Overview

Brought to you by YData

Dataset statistics

Number of variables	55
Number of observations	999
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	4.3 MiB
Average record size in memory	4.4 KiB

Variable types

Text	23
Numeric	1
Categorical	31

Alerts

`Authority_Present` is highly overall correlated with `Clarity_and_Conciseness_Value` and 30 other fields	High correlation
`Clarity_and_Conciseness_Value` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Contains_Colon` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Contains_Exclamation_Mark` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Contains_Hyphen` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Contains_Numbers` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Contains_Question_Mark` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Contains_Quotes` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Curiosity_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Economic_Benefit_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Emphatic_Capitalization_Usage` is highly overall correlated with `Authority_Present` and 27 other fields	High correlation
`Ends_With_Question_Mark` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Exclusivity_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Exclusivity_Words` is highly overall correlated with `Authority_Present` and 27 other fields	High correlation
`Fear_Concern_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Hope_Optimism_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Indignation_Controversy_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Length_General_Assessment` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Main_Category` is highly overall correlated with `Authority_Present` and 27 other fields	High correlation
`Main_Classification` is highly overall correlated with `Authority_Present` and 27 other fields	High correlation
`National_Relevance_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Originality_and_Differentiation_Value` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Personal_Identification_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Prohibition_Restriction_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Recognized_Brand_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Relevance_and_Timeliness_Value` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Solution_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Starts_With_Number` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Strategic_Keyword_Usage_Value` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Surprise_Awe_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Temporal_Urgency_Present` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Visibility` is highly overall correlated with `Authority_Present` and 30 other fields	High correlation
`Clarity_and_Conciseness_Value` is highly imbalanced (85.7%)	Imbalance
`Relevance_and_Timeliness_Value` is highly imbalanced (75.0%)	Imbalance
`Strategic_Keyword_Usage_Value` is highly imbalanced (75.5%)	Imbalance
`Contains_Question_Mark` is highly imbalanced (84.0%)	Imbalance
`Contains_Colon` is highly imbalanced (71.3%)	Imbalance
`Contains_Exclamation_Mark` is highly imbalanced (91.4%)	Imbalance
`Starts_With_Number` is highly imbalanced (79.6%)	Imbalance
`Ends_With_Question_Mark` is highly imbalanced (85.5%)	Imbalance
`Length_General_Assessment` is highly imbalanced (80.6%)	Imbalance
`Emphatic_Capitalization_Usage` is highly imbalanced (91.1%)	Imbalance
`Main_Classification` is highly imbalanced (50.6%)	Imbalance
`Temporal_Urgency_Present` is highly imbalanced (53.1%)	Imbalance
`Exclusivity_Present` is highly imbalanced (76.9%)	Imbalance
`Exclusivity_Words` is highly imbalanced (89.0%)	Imbalance
`Solution_Present` is highly imbalanced (56.0%)	Imbalance
`Prohibition_Restriction_Present` is highly imbalanced (64.5%)	Imbalance
`Visibility` has unique values	Unique

Reproduction

Analysis started	2025-07-07 08:48:30.495794
Analysis finished	2025-07-07 08:48:48.965837
Duration	18.47 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

Title
Text

Distinct	983
Distinct (%)	98.4%
Missing	0
Missing (%)	0.0%
Memory size	157.4 KiB

Length

Max length	189
Median length	109
Mean length	73.832833
Min length	18

Characters and Unicode

Total characters	73759
Distinct characters	88
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	967 ?
Unique (%)	96.8%

Sample

1st row	British jets intercept 15 Russian military aircraft
2nd row	New driveway rule change affecting every home in England has begun
3rd row	The historic English city that is the best day trip within one hour of London
4th row	David Mitchell convicted for covering road with potatoes and silt
5th row	Say goodbye to parasols – Tesco is selling a smarter option that covers your entire outdoor space better

Value	Count	Frequency (%)
to	429	3.4%
in	268	2.1%
the	210	1.7%
and	199	1.6%
of	197	1.6%
for	194	1.6%
with	138	1.1%
uk	133	1.1%
as	131	1.1%
on	120	1.0%
Other values (3420)	10454	83.8%

Most occurring characters

Value	Count	Frequency (%)
	11474	15.6%
e	6781	9.2%
a	4706	6.4%
t	4589	6.2%
n	4361	5.9%
s	4321	5.9%
o	4310	5.8%
r	4187	5.7%
i	3887	5.3%
l	2625	3.6%
Other values (78)	22518	30.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	73759	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	11474	15.6%
e	6781	9.2%
a	4706	6.4%
t	4589	6.2%
n	4361	5.9%
s	4321	5.9%
o	4310	5.8%
r	4187	5.7%
i	3887	5.3%
l	2625	3.6%
Other values (78)	22518	30.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	73759	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	11474	15.6%
e	6781	9.2%
a	4706	6.4%
t	4589	6.2%
n	4361	5.9%
s	4321	5.9%
o	4310	5.8%
r	4187	5.7%
i	3887	5.3%
l	2625	3.6%
Other values (78)	22518	30.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	73759	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	11474	15.6%
e	6781	9.2%
a	4706	6.4%
t	4589	6.2%
n	4361	5.9%
s	4321	5.9%
o	4310	5.8%
r	4187	5.7%
i	3887	5.3%
l	2625	3.6%
Other values (78)	22518	30.5%

Visibility
Real number (ℝ)

High correlation Unique

Distinct	999
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1331401.1

Minimum	316132
Maximum	10893901
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	316132
5-th percentile	339486.6
Q1	456888.5
median	752044
Q3	1512781
95-th percentile	4327268.2
Maximum	10893901
Range	10577769
Interquartile range (IQR)	1055892.5

Descriptive statistics

Standard deviation	1526279.8
Coefficient of variation (CV)	1.1463711
Kurtosis	11.171185
Mean	1331401.1
Median Absolute Deviation (MAD)	350735
Skewness	3.0255473
Sum	1.3300697 × 10⁹
Variance	2.3295299 × 10¹²
Monotonicity	Strictly decreasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
316132	1	0.1%
10893901	1	0.1%
10439139	1	0.1%
10098169	1	0.1%
10031250	1	0.1%
9765281	1	0.1%
9557677	1	0.1%
324058	1	0.1%
324091	1	0.1%
325259	1	0.1%
Other values (989)	989	99.0%

Value	Count	Frequency (%)
316132	1	0.1%
316533	1	0.1%
317591	1	0.1%
317685	1	0.1%
317796	1	0.1%
318074	1	0.1%
318561	1	0.1%
319337	1	0.1%
319502	1	0.1%
320207	1	0.1%

Value	Count	Frequency (%)
10893901	1	0.1%
10439139	1	0.1%
10098169	1	0.1%
10031250	1	0.1%
9765281	1	0.1%
9557677	1	0.1%
9470424	1	0.1%
9365831	1	0.1%
9220647	1	0.1%
9175453	1	0.1%

Cleaned_Headline
Text

Distinct	982
Distinct (%)	98.3%
Missing	0
Missing (%)	0.0%
Memory size	155.0 KiB

Length

Max length	189
Median length	109
Mean length	72.362362
Min length	0

Characters and Unicode

Total characters	72290
Distinct characters	86
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	980 ?
Unique (%)	98.1%

Sample

1st row	British jets intercept 15 Russian military aircraft
2nd row	New driveway rule change affecting every home in England has begun
3rd row	The historic English city that is the best day trip within one hour of London
4th row	David Mitchell convicted for covering road with potatoes and silt
5th row	Say goodbye to parasols – Tesco is selling a smarter option that covers your entire outdoor space better

Value	Count	Frequency (%)
to	424	3.5%
in	263	2.2%
the	209	1.7%
of	196	1.6%
and	194	1.6%
for	185	1.5%
with	135	1.1%
uk	131	1.1%
as	127	1.0%
on	118	1.0%
Other values (3411)	10248	83.8%

Most occurring characters

Value	Count	Frequency (%)
	11248	15.6%
e	6652	9.2%
a	4615	6.4%
t	4513	6.2%
n	4268	5.9%
o	4238	5.9%
s	4224	5.8%
r	4113	5.7%
i	3826	5.3%
l	2576	3.6%
Other values (76)	22017	30.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	72290	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	11248	15.6%
e	6652	9.2%
a	4615	6.4%
t	4513	6.2%
n	4268	5.9%
o	4238	5.9%
s	4224	5.8%
r	4113	5.7%
i	3826	5.3%
l	2576	3.6%
Other values (76)	22017	30.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	72290	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	11248	15.6%
e	6652	9.2%
a	4615	6.4%
t	4513	6.2%
n	4268	5.9%
o	4238	5.9%
s	4224	5.8%
r	4113	5.7%
i	3826	5.3%
l	2576	3.6%
Other values (76)	22017	30.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	72290	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	11248	15.6%
e	6652	9.2%
a	4615	6.4%
t	4513	6.2%
n	4268	5.9%
o	4238	5.9%
s	4224	5.8%
r	4113	5.7%
i	3826	5.3%
l	2576	3.6%
Other values (76)	22017	30.5%

Main_Category
Categorical

High correlation

Distinct	17
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	73.1 KiB

News_and_Current_Events	306
Finance_and_Business	176
Travel	95
Entertainment_and_Culture	92
Home_and_Lifestyle	75
Other values (12)	255

Length

Max length	26
Median length	23
Mean length	17.796797
Min length	0

Characters and Unicode

Total characters	17779
Distinct characters	36
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	0.2%

Sample

1st row	News_and_Current_Events
2nd row	News_and_Current_Events
3rd row	Travel
4th row	News_and_Current_Events
5th row	Home_and_Lifestyle

Common Values

Value	Count	Frequency (%)
News_and_Current_Events	306	30.6%
Finance_and_Business	176	17.6%
Travel	95	9.5%
Entertainment_and_Culture	92	9.2%
Home_and_Lifestyle	75	7.5%
Public_Safety	47	4.7%
Sports	40	4.0%
Health_and_Wellness	33	3.3%
Science	30	3.0%
Gastronomy	25	2.5%
Other values (7)	80	8.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
news_and_current_events	306	31.2%
finance_and_business	176	17.9%
travel	95	9.7%
entertainment_and_culture	92	9.4%
home_and_lifestyle	75	7.6%
public_safety	47	4.8%
sports	40	4.1%
health_and_wellness	33	3.4%
science	30	3.1%
gastronomy	25	2.5%
Other values (6)	63	6.4%

Most occurring characters

Value	Count	Frequency (%)
n	2284	12.8%
e	2145	12.1%
_	1785	10.0%
s	1439	8.1%
t	1234	6.9%
a	1232	6.9%
r	980	5.5%
u	758	4.3%
d	738	4.2%
i	725	4.1%
Other values (26)	4459	25.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	17779	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	2284	12.8%
e	2145	12.1%
_	1785	10.0%
s	1439	8.1%
t	1234	6.9%
a	1232	6.9%
r	980	5.5%
u	758	4.3%
d	738	4.2%
i	725	4.1%
Other values (26)	4459	25.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	17779	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	2284	12.8%
e	2145	12.1%
_	1785	10.0%
s	1439	8.1%
t	1234	6.9%
a	1232	6.9%
r	980	5.5%
u	758	4.3%
d	738	4.2%
i	725	4.1%
Other values (26)	4459	25.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	17779	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	2284	12.8%
e	2145	12.1%
_	1785	10.0%
s	1439	8.1%
t	1234	6.9%
a	1232	6.9%
r	980	5.5%
u	758	4.3%
d	738	4.2%
i	725	4.1%
Other values (26)	4459	25.1%

Subcategory_1
Text

Distinct	106
Distinct (%)	10.6%
Missing	0
Missing (%)	0.0%
Memory size	70.8 KiB

Length

Max length	33
Median length	26
Mean length	15.439439
Min length	0

Characters and Unicode

Total characters	15424
Distinct characters	54
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	49 ?
Unique (%)	4.9%

Sample

1st row	International
2nd row	Government
3rd row	Destinations
4th row	Crime & Judicial
5th row	Gardening_and_Plants

Value	Count	Frequency (%)
	320	17.5%
personal	92	5.0%
finance	92	5.0%
politics	85	4.7%
destinations	62	3.4%
international	62	3.4%
environment	59	3.2%
celebrities	59	3.2%
influencers	59	3.2%
prevention	53	2.9%
Other values (130)	882	48.3%

Most occurring characters

Value	Count	Frequency (%)
n	1743	11.3%
e	1560	10.1%
i	1397	9.1%
r	987	6.4%
s	973	6.3%
a	971	6.3%
t	958	6.2%
	843	5.5%
o	818	5.3%
l	765	5.0%
Other values (44)	4409	28.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	15424	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	1743	11.3%
e	1560	10.1%
i	1397	9.1%
r	987	6.4%
s	973	6.3%
a	971	6.3%
t	958	6.2%
	843	5.5%
o	818	5.3%
l	765	5.0%
Other values (44)	4409	28.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	15424	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	1743	11.3%
e	1560	10.1%
i	1397	9.1%
r	987	6.4%
s	973	6.3%
a	971	6.3%
t	958	6.2%
	843	5.5%
o	818	5.3%
l	765	5.0%
Other values (44)	4409	28.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	15424	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	1743	11.3%
e	1560	10.1%
i	1397	9.1%
r	987	6.4%
s	973	6.3%
a	971	6.3%
t	958	6.2%
	843	5.5%
o	818	5.3%
l	765	5.0%
Other values (44)	4409	28.6%

Subcategory_2
Text

Distinct	113
Distinct (%)	11.3%
Missing	0
Missing (%)	0.0%
Memory size	61.0 KiB

Length

Max length	28
Median length	3
Mean length	5.3683684
Min length	0

Characters and Unicode

Total characters	5363
Distinct characters	49
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	78 ?
Unique (%)	7.8%

Sample

1st row	N/A
2nd row	N/A
3rd row	Guides
4th row	N/A
5th row	N/A

Value	Count	Frequency (%)
n/a	638	59.4%
government	62	5.8%
tips	43	4.0%
national	32	3.0%
guides	26	2.4%
	19	1.8%
international	16	1.5%
prevention	11	1.0%
transfers	9	0.8%
main	7	0.7%
Other values (125)	211	19.6%

Most occurring characters

Value	Count	Frequency (%)
N	676	12.6%
A	660	12.3%
/	639	11.9%
e	422	7.9%
n	342	6.4%
i	283	5.3%
t	260	4.8%
s	256	4.8%
r	215	4.0%
a	215	4.0%
Other values (39)	1395	26.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5363	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	676	12.6%
A	660	12.3%
/	639	11.9%
e	422	7.9%
n	342	6.4%
i	283	5.3%
t	260	4.8%
s	256	4.8%
r	215	4.0%
a	215	4.0%
Other values (39)	1395	26.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5363	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	676	12.6%
A	660	12.3%
/	639	11.9%
e	422	7.9%
n	342	6.4%
i	283	5.3%
t	260	4.8%
s	256	4.8%
r	215	4.0%
a	215	4.0%
Other values (39)	1395	26.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5363	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	676	12.6%
A	660	12.3%
/	639	11.9%
e	422	7.9%
n	342	6.4%
i	283	5.3%
t	260	4.8%
s	256	4.8%
r	215	4.0%
a	215	4.0%
Other values (39)	1395	26.0%

Clarity_and_Conciseness_Value
Categorical

High correlation Imbalance

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	59.6 KiB

High	960
Medium	20
	17
Low	2

Length

Max length	6
Median length	4
Mean length	3.96997
Min length	0

Characters and Unicode

Total characters	3966
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	High
2nd row	High
3rd row	High
4th row	High
5th row	High

Common Values

Value	Count	Frequency (%)
High	960	96.1%
Medium	20	2.0%
	17	1.7%
Low	2	0.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
high	960	97.8%
medium	20	2.0%
low	2	0.2%

Most occurring characters

Value	Count	Frequency (%)
i	980	24.7%
H	960	24.2%
g	960	24.2%
h	960	24.2%
M	20	0.5%
e	20	0.5%
d	20	0.5%
u	20	0.5%
m	20	0.5%
L	2	0.1%
Other values (2)	4	0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3966	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	980	24.7%
H	960	24.2%
g	960	24.2%
h	960	24.2%
M	20	0.5%
e	20	0.5%
d	20	0.5%
u	20	0.5%
m	20	0.5%
L	2	0.1%
Other values (2)	4	0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3966	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	980	24.7%
H	960	24.2%
g	960	24.2%
h	960	24.2%
M	20	0.5%
e	20	0.5%
d	20	0.5%
u	20	0.5%
m	20	0.5%
L	2	0.1%
Other values (2)	4	0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3966	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	980	24.7%
H	960	24.2%
g	960	24.2%
h	960	24.2%
M	20	0.5%
e	20	0.5%
d	20	0.5%
u	20	0.5%
m	20	0.5%
L	2	0.1%
Other values (2)	4	0.1%

Clarity_and_Conciseness_Comment
Text

Distinct	804
Distinct (%)	80.5%
Missing	0
Missing (%)	0.0%
Memory size	140.9 KiB

Length

Max length	222
Median length	145
Mean length	86.192192
Min length	0

Characters and Unicode

Total characters	86106
Distinct characters	73
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	770 ?
Unique (%)	77.1%

Sample

1st row	The headline is direct and clearly states the event without ambiguity.
2nd row	The headline is direct and easy to understand, clearly stating the what, who, and where.
3rd row	The main message is very clear and easy to understand, directly stating the topic.
4th row	The headline clearly states who was convicted and for what unusual reason.
5th row	The main message is straightforward and easy to grasp.

Value	Count	Frequency (%)
the	1639	11.7%
and	1168	8.4%
is	884	6.3%
to	625	4.5%
message	608	4.3%
main	565	4.0%
easy	541	3.9%
understand	533	3.8%
clear	530	3.8%
headline	345	2.5%
Other values (1433)	6540	46.8%

Most occurring characters

Value	Count	Frequency (%)
	12996	15.1%
e	9584	11.1%
a	7519	8.7%
t	5871	6.8%
n	5719	6.6%
s	5674	6.6%
i	5319	6.2%
d	3861	4.5%
r	3757	4.4%
o	2843	3.3%
Other values (63)	22963	26.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	86106	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	12996	15.1%
e	9584	11.1%
a	7519	8.7%
t	5871	6.8%
n	5719	6.6%
s	5674	6.6%
i	5319	6.2%
d	3861	4.5%
r	3757	4.4%
o	2843	3.3%
Other values (63)	22963	26.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	86106	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	12996	15.1%
e	9584	11.1%
a	7519	8.7%
t	5871	6.8%
n	5719	6.6%
s	5674	6.6%
i	5319	6.2%
d	3861	4.5%
r	3757	4.4%
o	2843	3.3%
Other values (63)	22963	26.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	86106	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	12996	15.1%
e	9584	11.1%
a	7519	8.7%
t	5871	6.8%
n	5719	6.6%
s	5674	6.6%
i	5319	6.2%
d	3861	4.5%
r	3757	4.4%
o	2843	3.3%
Other values (63)	22963	26.7%

Relevance_and_Timeliness_Value
Categorical

High correlation Imbalance

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	59.7 KiB

High	915
Medium	63
	17
Low	4

Length

Max length	6
Median length	4
Mean length	4.0540541
Min length	0

Characters and Unicode

Total characters	4050
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	High
2nd row	High
3rd row	High
4th row	Low
5th row	High

Common Values

Value	Count	Frequency (%)
High	915	91.6%
Medium	63	6.3%
	17	1.7%
Low	4	0.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
high	915	93.2%
medium	63	6.4%
low	4	0.4%

Most occurring characters

Value	Count	Frequency (%)
i	978	24.1%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	63	1.6%
e	63	1.6%
d	63	1.6%
u	63	1.6%
m	63	1.6%
L	4	0.1%
Other values (2)	8	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4050	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	978	24.1%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	63	1.6%
e	63	1.6%
d	63	1.6%
u	63	1.6%
m	63	1.6%
L	4	0.1%
Other values (2)	8	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4050	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	978	24.1%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	63	1.6%
e	63	1.6%
d	63	1.6%
u	63	1.6%
m	63	1.6%
L	4	0.1%
Other values (2)	8	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4050	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	978	24.1%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	63	1.6%
e	63	1.6%
d	63	1.6%
u	63	1.6%
m	63	1.6%
L	4	0.1%
Other values (2)	8	0.2%

Relevance_and_Timeliness_Comment
Text

Distinct	983
Distinct (%)	98.4%
Missing	0
Missing (%)	0.0%
Memory size	162.8 KiB

Length

Max length	237
Median length	155
Mean length	109.7047
Min length	0

Characters and Unicode

Total characters	109595
Distinct characters	68
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	982 ?
Unique (%)	98.3%

Sample

1st row	Covers a geopolitically relevant and timely topic concerning international military activities.
2nd row	The use of 'New' and 'has begun' creates a sense of immediacy and relevance for the target audience.
3rd row	Day trips and proximity to major cities like London are evergreen topics with high interest.
4th row	The event is localized and not tied to a major ongoing news trend, making its general relevance low.
5th row	The topic of outdoor space solutions is relevant, especially during warmer seasons, and appeals to practical home improvement interests.

Value	Count	Frequency (%)
and	1109	6.7%
a	765	4.7%
relevant	615	3.7%
the	567	3.4%
of	503	3.1%
to	493	3.0%
highly	465	2.8%
is	369	2.2%
interest	347	2.1%
are	335	2.0%
Other values (1767)	10875	66.1%

Most occurring characters

Value	Count	Frequency (%)
	15461	14.1%
e	12197	11.1%
i	8018	7.3%
n	7943	7.2%
a	7725	7.0%
t	7283	6.6%
r	5836	5.3%
s	5494	5.0%
o	4999	4.6%
l	4837	4.4%
Other values (58)	29802	27.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	109595	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	15461	14.1%
e	12197	11.1%
i	8018	7.3%
n	7943	7.2%
a	7725	7.0%
t	7283	6.6%
r	5836	5.3%
s	5494	5.0%
o	4999	4.6%
l	4837	4.4%
Other values (58)	29802	27.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	109595	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	15461	14.1%
e	12197	11.1%
i	8018	7.3%
n	7943	7.2%
a	7725	7.0%
t	7283	6.6%
r	5836	5.3%
s	5494	5.0%
o	4999	4.6%
l	4837	4.4%
Other values (58)	29802	27.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	109595	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	15461	14.1%
e	12197	11.1%
i	8018	7.3%
n	7943	7.2%
a	7725	7.0%
t	7283	6.6%
r	5836	5.3%
s	5494	5.0%
o	4999	4.6%
l	4837	4.4%
Other values (58)	29802	27.2%

Strategic_Keyword_Usage_Value
Categorical

High correlation Imbalance

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	59.7 KiB

High	915
Medium	65
	17
Low	2

Length

Max length	6
Median length	4
Mean length	4.0600601
Min length	0

Characters and Unicode

Total characters	4056
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	High
2nd row	High
3rd row	High
4th row	Low
5th row	High

Common Values

Value	Count	Frequency (%)
High	915	91.6%
Medium	65	6.5%
	17	1.7%
Low	2	0.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
high	915	93.2%
medium	65	6.6%
low	2	0.2%

Most occurring characters

Value	Count	Frequency (%)
i	980	24.2%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	65	1.6%
e	65	1.6%
d	65	1.6%
u	65	1.6%
m	65	1.6%
L	2	< 0.1%
Other values (2)	4	0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4056	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	980	24.2%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	65	1.6%
e	65	1.6%
d	65	1.6%
u	65	1.6%
m	65	1.6%
L	2	< 0.1%
Other values (2)	4	0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4056	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	980	24.2%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	65	1.6%
e	65	1.6%
d	65	1.6%
u	65	1.6%
m	65	1.6%
L	2	< 0.1%
Other values (2)	4	0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4056	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	980	24.2%
H	915	22.6%
g	915	22.6%
h	915	22.6%
M	65	1.6%
e	65	1.6%
d	65	1.6%
u	65	1.6%
m	65	1.6%
L	2	< 0.1%
Other values (2)	4	0.1%

Strategic_Keyword_Usage_Comment
Text

Distinct	983
Distinct (%)	98.4%
Missing	0
Missing (%)	0.0%
Memory size	188.4 KiB

Length

Max length	244
Median length	170
Mean length	123.0991
Min length	0

Characters and Unicode

Total characters	122976
Distinct characters	80
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	982 ?
Unique (%)	98.3%

Sample

1st row	Uses clear, descriptive keywords like 'British jets', 'intercept', 'Russian military aircraft' which are highly relevant to the topic and discoverable.
2nd row	Uses specific and relevant keywords like 'driveway rule change' and 'England' that directly target a specific audience's potential interests.
3rd row	Uses highly relevant keywords like "historic English city," "best day trip," and "one hour of London" which are likely search terms.
4th row	The keywords are too specific to the event and do not align with common search queries.
5th row	Keywords like "parasols", "Tesco", and "outdoor space" are relevant to the topic and target audience.

Value	Count	Frequency (%)
and	1547	8.8%
relevant	779	4.4%
keywords	767	4.3%
like	748	4.2%
are	731	4.1%
highly	520	2.9%
uses	519	2.9%
to	463	2.6%
the	435	2.5%
audience	329	1.9%
Other values (2593)	10831	61.3%

Most occurring characters

Value	Count	Frequency (%)
	16691	13.6%
e	13262	10.8%
a	8660	7.0%
r	7072	5.8%
t	6826	5.6%
n	6727	5.5%
s	6392	5.2%
i	6164	5.0%
l	5113	4.2%
o	4675	3.8%
Other values (70)	41394	33.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	122976	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	16691	13.6%
e	13262	10.8%
a	8660	7.0%
r	7072	5.8%
t	6826	5.6%
n	6727	5.5%
s	6392	5.2%
i	6164	5.0%
l	5113	4.2%
o	4675	3.8%
Other values (70)	41394	33.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	122976	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	16691	13.6%
e	13262	10.8%
a	8660	7.0%
r	7072	5.8%
t	6826	5.6%
n	6727	5.5%
s	6392	5.2%
i	6164	5.0%
l	5113	4.2%
o	4675	3.8%
Other values (70)	41394	33.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	122976	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	16691	13.6%
e	13262	10.8%
a	8660	7.0%
r	7072	5.8%
t	6826	5.6%
n	6727	5.5%
s	6392	5.2%
i	6164	5.0%
l	5113	4.2%
o	4675	3.8%
Other values (70)	41394	33.7%

Originality_and_Differentiation_Value
Categorical

High correlation

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	60.9 KiB

Medium	745
High	156
Low	81
	17

Length

Max length	6
Median length	6
Mean length	5.3423423
Min length	0

Characters and Unicode

Total characters	5337
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Medium
2nd row	Medium
3rd row	Medium
4th row	High
5th row	High

Common Values

Value	Count	Frequency (%)
Medium	745	74.6%
High	156	15.6%
Low	81	8.1%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
medium	745	75.9%
high	156	15.9%
low	81	8.2%

Most occurring characters

Value	Count	Frequency (%)
i	901	16.9%
M	745	14.0%
e	745	14.0%
d	745	14.0%
u	745	14.0%
m	745	14.0%
H	156	2.9%
g	156	2.9%
h	156	2.9%
L	81	1.5%
Other values (2)	162	3.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5337	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	901	16.9%
M	745	14.0%
e	745	14.0%
d	745	14.0%
u	745	14.0%
m	745	14.0%
H	156	2.9%
g	156	2.9%
h	156	2.9%
L	81	1.5%
Other values (2)	162	3.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5337	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	901	16.9%
M	745	14.0%
e	745	14.0%
d	745	14.0%
u	745	14.0%
m	745	14.0%
H	156	2.9%
g	156	2.9%
h	156	2.9%
L	81	1.5%
Other values (2)	162	3.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5337	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	901	16.9%
M	745	14.0%
e	745	14.0%
d	745	14.0%
u	745	14.0%
m	745	14.0%
H	156	2.9%
g	156	2.9%
h	156	2.9%
L	81	1.5%
Other values (2)	162	3.0%

Originality_and_Differentiation_Comment
Text

Distinct	983
Distinct (%)	98.4%
Missing	0
Missing (%)	0.0%
Memory size	182.4 KiB

Length

Max length	270
Median length	175
Mean length	124.00501
Min length	0

Characters and Unicode

Total characters	123881
Distinct characters	82
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	982 ?
Unique (%)	98.3%

Sample

1st row	While the event is specific, the phrasing is fairly standard for news reporting on military interceptions.
2nd row	While the topic is specific, the headline's structure is quite common for news alerts, lacking a highly unique angle.
3rd row	While "best day trip" is a common superlative, the specific geographic and historical context provides some differentiation.
4th row	The bizarre nature of the crime (covering a road with potatoes and silt) makes the headline highly original and memorable.
5th row	The headline positions the product as a "smarter option" and an improvement over traditional parasols, offering a unique angle.

Value	Count	Frequency (%)
the	1599	8.2%
a	1131	5.8%
is	800	4.1%
and	598	3.1%
specific	543	2.8%
unique	528	2.7%
of	503	2.6%
common	493	2.5%
while	461	2.4%
angle	381	2.0%
Other values (2241)	12394	63.8%

Most occurring characters

Value	Count	Frequency (%)
	18449	14.9%
e	12094	9.8%
i	9785	7.9%
t	8349	6.7%
n	8087	6.5%
a	7890	6.4%
o	6325	5.1%
s	6100	4.9%
r	5446	4.4%
c	4285	3.5%
Other values (72)	37071	29.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	123881	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	18449	14.9%
e	12094	9.8%
i	9785	7.9%
t	8349	6.7%
n	8087	6.5%
a	7890	6.4%
o	6325	5.1%
s	6100	4.9%
r	5446	4.4%
c	4285	3.5%
Other values (72)	37071	29.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	123881	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	18449	14.9%
e	12094	9.8%
i	9785	7.9%
t	8349	6.7%
n	8087	6.5%
a	7890	6.4%
o	6325	5.1%
s	6100	4.9%
r	5446	4.4%
c	4285	3.5%
Other values (72)	37071	29.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	123881	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	18449	14.9%
e	12094	9.8%
i	9785	7.9%
t	8349	6.7%
n	8087	6.5%
a	7890	6.4%
o	6325	5.1%
s	6100	4.9%
r	5446	4.4%
c	4285	3.5%
Other values (72)	37071	29.9%

Contains_Numbers
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	58.1 KiB

No	518
Yes	464
	17

Length

Max length	3
Median length	2
Mean length	2.4304304
Min length	0

Characters and Unicode

Total characters	2428
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Yes
2nd row	No
3rd row	Yes
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	518	51.9%
Yes	464	46.4%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	518	52.7%
yes	464	47.3%

Most occurring characters

Value	Count	Frequency (%)
N	518	21.3%
o	518	21.3%
Y	464	19.1%
e	464	19.1%
s	464	19.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2428	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	518	21.3%
o	518	21.3%
Y	464	19.1%
e	464	19.1%
s	464	19.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2428	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	518	21.3%
o	518	21.3%
Y	464	19.1%
e	464	19.1%
s	464	19.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2428	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	518	21.3%
o	518	21.3%
Y	464	19.1%
e	464	19.1%
s	464	19.1%

Contains_Quotes
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.9 KiB

No	782
Yes	200
	17

Length

Max length	3
Median length	2
Mean length	2.1661662
Min length	0

Characters and Unicode

Total characters	2164
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	782	78.3%
Yes	200	20.0%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	782	79.6%
yes	200	20.4%

Most occurring characters

Value	Count	Frequency (%)
N	782	36.1%
o	782	36.1%
Y	200	9.2%
e	200	9.2%
s	200	9.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2164	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	782	36.1%
o	782	36.1%
Y	200	9.2%
e	200	9.2%
s	200	9.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2164	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	782	36.1%
o	782	36.1%
Y	200	9.2%
e	200	9.2%
s	200	9.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2164	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	782	36.1%
o	782	36.1%
Y	200	9.2%
e	200	9.2%
s	200	9.2%

Contains_Question_Mark
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

No	964
Yes	18
	17

Length

Max length	3
Median length	2
Mean length	1.983984
Min length	0

Characters and Unicode

Total characters	1982
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	964	96.5%
Yes	18	1.8%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	964	98.2%
yes	18	1.8%

Most occurring characters

Value	Count	Frequency (%)
N	964	48.6%
o	964	48.6%
Y	18	0.9%
e	18	0.9%
s	18	0.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1982	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	964	48.6%
o	964	48.6%
Y	18	0.9%
e	18	0.9%
s	18	0.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1982	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	964	48.6%
o	964	48.6%
Y	18	0.9%
e	18	0.9%
s	18	0.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1982	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	964	48.6%
o	964	48.6%
Y	18	0.9%
e	18	0.9%
s	18	0.9%

Contains_Colon
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

No	921
Yes	61
	17

Length

Max length	3
Median length	2
Mean length	2.027027
Min length	0

Characters and Unicode

Total characters	2025
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	921	92.2%
Yes	61	6.1%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	921	93.8%
yes	61	6.2%

Most occurring characters

Value	Count	Frequency (%)
N	921	45.5%
o	921	45.5%
Y	61	3.0%
e	61	3.0%
s	61	3.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2025	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	921	45.5%
o	921	45.5%
Y	61	3.0%
e	61	3.0%
s	61	3.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2025	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	921	45.5%
o	921	45.5%
Y	61	3.0%
e	61	3.0%
s	61	3.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2025	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	921	45.5%
o	921	45.5%
Y	61	3.0%
e	61	3.0%
s	61	3.0%

Contains_Hyphen
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.9 KiB

No	780
Yes	202
	17

Length

Max length	3
Median length	2
Mean length	2.1681682
Min length	0

Characters and Unicode

Total characters	2166
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	Yes

Common Values

Value	Count	Frequency (%)
No	780	78.1%
Yes	202	20.2%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	780	79.4%
yes	202	20.6%

Most occurring characters

Value	Count	Frequency (%)
N	780	36.0%
o	780	36.0%
Y	202	9.3%
e	202	9.3%
s	202	9.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2166	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	780	36.0%
o	780	36.0%
Y	202	9.3%
e	202	9.3%
s	202	9.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2166	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	780	36.0%
o	780	36.0%
Y	202	9.3%
e	202	9.3%
s	202	9.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2166	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	780	36.0%
o	780	36.0%
Y	202	9.3%
e	202	9.3%
s	202	9.3%

Contains_Exclamation_Mark
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

No	981
	17
Yes	1

Length

Max length	3
Median length	2
Mean length	1.966967
Min length	0

Characters and Unicode

Total characters	1965
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	981	98.2%
	17	1.7%
Yes	1	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	981	99.9%
yes	1	0.1%

Most occurring characters

Value	Count	Frequency (%)
N	981	49.9%
o	981	49.9%
Y	1	0.1%
e	1	0.1%
s	1	0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1965	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	981	49.9%
o	981	49.9%
Y	1	0.1%
e	1	0.1%
s	1	0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1965	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	981	49.9%
o	981	49.9%
Y	1	0.1%
e	1	0.1%
s	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1965	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	981	49.9%
o	981	49.9%
Y	1	0.1%
e	1	0.1%
s	1	0.1%

Starts_With_Number
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

No	951
Yes	31
	17

Length

Max length	3
Median length	2
Mean length	1.996997
Min length	0

Characters and Unicode

Total characters	1995
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	951	95.2%
Yes	31	3.1%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	951	96.8%
yes	31	3.2%

Most occurring characters

Value	Count	Frequency (%)
N	951	47.7%
o	951	47.7%
Y	31	1.6%
e	31	1.6%
s	31	1.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1995	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	951	47.7%
o	951	47.7%
Y	31	1.6%
e	31	1.6%
s	31	1.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1995	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	951	47.7%
o	951	47.7%
Y	31	1.6%
e	31	1.6%
s	31	1.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1995	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	951	47.7%
o	951	47.7%
Y	31	1.6%
e	31	1.6%
s	31	1.6%

Ends_With_Question_Mark
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

No	968
	17
Yes	14

Length

Max length	3
Median length	2
Mean length	1.97998
Min length	0

Characters and Unicode

Total characters	1978
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	968	96.9%
	17	1.7%
Yes	14	1.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	968	98.6%
yes	14	1.4%

Most occurring characters

Value	Count	Frequency (%)
N	968	48.9%
o	968	48.9%
Y	14	0.7%
e	14	0.7%
s	14	0.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1978	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	968	48.9%
o	968	48.9%
Y	14	0.7%
e	14	0.7%
s	14	0.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1978	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	968	48.9%
o	968	48.9%
Y	14	0.7%
e	14	0.7%
s	14	0.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1978	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	968	48.9%
o	968	48.9%
Y	14	0.7%
e	14	0.7%
s	14	0.7%

Length_General_Assessment
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	64.0 KiB

Adequate	954
Too long, risk of truncation	28
	17

Length

Max length	28
Median length	8
Mean length	8.4244244
Min length	0

Characters and Unicode

Total characters	8416
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Adequate
2nd row	Adequate
3rd row	Adequate
4th row	Adequate
5th row	Adequate

Common Values

Value	Count	Frequency (%)
Adequate	954	95.5%
Too long, risk of truncation	28	2.8%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
adequate	954	87.2%
too	28	2.6%
long	28	2.6%
risk	28	2.6%
of	28	2.6%
truncation	28	2.6%

Most occurring characters

Value	Count	Frequency (%)
e	1908	22.7%
t	1010	12.0%
u	982	11.7%
a	982	11.7%
q	954	11.3%
d	954	11.3%
A	954	11.3%
o	140	1.7%
	112	1.3%
n	84	1.0%
Other values (10)	336	4.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8416	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1908	22.7%
t	1010	12.0%
u	982	11.7%
a	982	11.7%
q	954	11.3%
d	954	11.3%
A	954	11.3%
o	140	1.7%
	112	1.3%
n	84	1.0%
Other values (10)	336	4.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8416	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1908	22.7%
t	1010	12.0%
u	982	11.7%
a	982	11.7%
q	954	11.3%
d	954	11.3%
A	954	11.3%
o	140	1.7%
	112	1.3%
n	84	1.0%
Other values (10)	336	4.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8416	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1908	22.7%
t	1010	12.0%
u	982	11.7%
a	982	11.7%
q	954	11.3%
d	954	11.3%
A	954	11.3%
o	140	1.7%
	112	1.3%
n	84	1.0%
Other values (10)	336	4.0%

Length_Number_of_Characters
Text

Distinct	98
Distinct (%)	9.8%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

Length

Max length	3
Median length	2
Mean length	2.013013
Min length	0

Characters and Unicode

Total characters	2011
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	19 ?
Unique (%)	1.9%

Sample

1st row	46
2nd row	68
3rd row	69
4th row	65
5th row	84

Value	Count	Frequency (%)
70	48	4.9%
69	46	4.7%
68	44	4.5%
66	42	4.3%
59	40	4.1%
75	39	4.0%
64	35	3.6%
60	34	3.5%
73	30	3.1%
50	26	2.6%
Other values (87)	598	60.9%

Most occurring characters

Value	Count	Frequency (%)
6	378	18.8%
7	322	16.0%
5	241	12.0%
8	218	10.8%
9	213	10.6%
4	175	8.7%
0	169	8.4%
1	121	6.0%
3	98	4.9%
2	76	3.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2011	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
6	378	18.8%
7	322	16.0%
5	241	12.0%
8	218	10.8%
9	213	10.6%
4	175	8.7%
0	169	8.4%
1	121	6.0%
3	98	4.9%
2	76	3.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2011	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
6	378	18.8%
7	322	16.0%
5	241	12.0%
8	218	10.8%
9	213	10.6%
4	175	8.7%
0	169	8.4%
1	121	6.0%
3	98	4.9%
2	76	3.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2011	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
6	378	18.8%
7	322	16.0%
5	241	12.0%
8	218	10.8%
9	213	10.6%
4	175	8.7%
0	169	8.4%
1	121	6.0%
3	98	4.9%
2	76	3.8%

Emphatic_Capitalization_Usage
Categorical

High correlation Imbalance

Distinct	26
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Memory size	59.2 KiB

No	956
	17
Yes, 'RETURN', seeks impact	2
Yes, 'DWP', justified use	2
Yes, 'AI Cameras', 'Repeat Offenders', seeks impact	1
Other values (21)	21

Length

Max length	151
Median length	2
Mean length	3.2222222
Min length	0

Characters and Unicode

Total characters	3219
Distinct characters	52
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	22 ?
Unique (%)	2.2%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	956	95.7%
	17	1.7%
Yes, 'RETURN', seeks impact	2	0.2%
Yes, 'DWP', justified use	2	0.2%
Yes, 'AI Cameras', 'Repeat Offenders', seeks impact	1	0.1%
Yes, 'Everything', seeks impact	1	0.1%
Yes, 'BBC', 'Strictly Come Dancing', justified use	1	0.1%
Yes, 'TODAY', justified use	1	0.1%
Yes, 'Essential Changes', seeks impact	1	0.1%
Yes, 'Say Goodbye To', seeks impact	1	0.1%
Other values (16)	16	1.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
no	956	83.0%
yes	26	2.3%
justified	13	1.1%
use	12	1.0%
impact	12	1.0%
seeks	11	1.0%
nouns	4	0.3%
and	4	0.3%
the	4	0.3%
proper	4	0.3%
Other values (87)	106	9.2%

Most occurring characters

Value	Count	Frequency (%)
o	1001	31.1%
N	959	29.8%
	170	5.3%
e	138	4.3%
s	107	3.3%
'	81	2.5%
i	77	2.4%
t	65	2.0%
,	64	2.0%
a	50	1.6%
Other values (42)	507	15.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3219	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	1001	31.1%
N	959	29.8%
	170	5.3%
e	138	4.3%
s	107	3.3%
'	81	2.5%
i	77	2.4%
t	65	2.0%
,	64	2.0%
a	50	1.6%
Other values (42)	507	15.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3219	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	1001	31.1%
N	959	29.8%
	170	5.3%
e	138	4.3%
s	107	3.3%
'	81	2.5%
i	77	2.4%
t	65	2.0%
,	64	2.0%
a	50	1.6%
Other values (42)	507	15.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3219	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	1001	31.1%
N	959	29.8%
	170	5.3%
e	138	4.3%
s	107	3.3%
'	81	2.5%
i	77	2.4%
t	65	2.0%
,	64	2.0%
a	50	1.6%
Other values (42)	507	15.8%

Main_Classification
Categorical

High correlation Imbalance

Distinct	26
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Memory size	74.7 KiB

Declarative Simple	645
Mystery/Revelation	66
Attribution ('according to', 'reveals')	50
Superlative ('best', 'worst')	29
Direct Quote	27
Other values (21)	182

Length

Max length	52
Median length	18
Mean length	19.478478
Min length	0

Characters and Unicode

Total characters	19459
Distinct characters	42
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6 ?
Unique (%)	0.6%

Sample

1st row	Declarative Simple
2nd row	Declarative Simple
3rd row	Superlative ('best', 'worst')
4th row	Declarative Simple
5th row	Comparative/Superlative

Common Values

Value	Count	Frequency (%)
Declarative Simple	645	64.6%
Mystery/Revelation	66	6.6%
Attribution ('according to', 'reveals')	50	5.0%
Superlative ('best', 'worst')	29	2.9%
Direct Quote	27	2.7%
List/Numbered	26	2.6%
List/Numbered ('5 ways')	19	1.9%
	17	1.7%
Direct Question	16	1.6%
Superlative	16	1.6%
Other values (16)	88	8.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
declarative	646	31.5%
simple	645	31.4%
mystery/revelation	80	3.9%
direct	68	3.3%
to	64	3.1%
according	64	3.1%
reveals	63	3.1%
attribution	51	2.5%
list/numbered	47	2.3%
superlative	45	2.2%
Other values (24)	281	13.7%

Most occurring characters

Value	Count	Frequency (%)
e	2765	14.2%
i	1813	9.3%
a	1603	8.2%
l	1483	7.6%
t	1476	7.6%
r	1207	6.2%
	1072	5.5%
c	885	4.5%
v	851	4.4%
D	715	3.7%
Other values (32)	5589	28.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	19459	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	2765	14.2%
i	1813	9.3%
a	1603	8.2%
l	1483	7.6%
t	1476	7.6%
r	1207	6.2%
	1072	5.5%
c	885	4.5%
v	851	4.4%
D	715	3.7%
Other values (32)	5589	28.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	19459	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	2765	14.2%
i	1813	9.3%
a	1603	8.2%
l	1483	7.6%
t	1476	7.6%
r	1207	6.2%
	1072	5.5%
c	885	4.5%
v	851	4.4%
D	715	3.7%
Other values (32)	5589	28.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	19459	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	2765	14.2%
i	1813	9.3%
a	1603	8.2%
l	1483	7.6%
t	1476	7.6%
r	1207	6.2%
	1072	5.5%
c	885	4.5%
v	851	4.4%
D	715	3.7%
Other values (32)	5589	28.7%

Comment_Type_Justification
Text

Distinct	978
Distinct (%)	97.9%
Missing	0
Missing (%)	0.0%
Memory size	178.8 KiB

Length

Max length	295
Median length	173
Mean length	125.14515
Min length	0

Characters and Unicode

Total characters	125020
Distinct characters	76
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	972 ?
Unique (%)	97.3%

Sample

1st row	It is a straightforward statement of fact, reporting an event without any special framing.
2nd row	The headline makes a direct statement about a new event or situation without asking a question or using sensational language.
3rd row	The headline uses the superlative "best" to describe the day trip experience.
4th row	The headline states a fact directly without questions, quotes, or other complex structures.
5th row	The headline compares a new "smarter option" to traditional "parasols", emphasizing its superior performance ("covers... better").

Value	Count	Frequency (%)
a	1848	9.8%
the	1474	7.8%
headline	928	4.9%
or	642	3.4%
without	523	2.8%
statement	457	2.4%
about	400	2.1%
question	381	2.0%
direct	373	2.0%
and	363	1.9%
Other values (1609)	11546	61.0%

Most occurring characters

Value	Count	Frequency (%)
	17953	14.4%
e	12895	10.3%
t	10865	8.7%
a	9153	7.3%
i	8878	7.1%
n	8041	6.4%
s	6632	5.3%
o	6307	5.0%
r	5641	4.5%
h	3983	3.2%
Other values (66)	34672	27.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	125020	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	17953	14.4%
e	12895	10.3%
t	10865	8.7%
a	9153	7.3%
i	8878	7.1%
n	8041	6.4%
s	6632	5.3%
o	6307	5.0%
r	5641	4.5%
h	3983	3.2%
Other values (66)	34672	27.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	125020	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	17953	14.4%
e	12895	10.3%
t	10865	8.7%
a	9153	7.3%
i	8878	7.1%
n	8041	6.4%
s	6632	5.3%
o	6307	5.0%
r	5641	4.5%
h	3983	3.2%
Other values (66)	34672	27.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	125020	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	17953	14.4%
e	12895	10.3%
t	10865	8.7%
a	9153	7.3%
i	8878	7.1%
n	8041	6.4%
s	6632	5.3%
o	6307	5.0%
r	5641	4.5%
h	3983	3.2%
Other values (66)	34672	27.7%

Temporal_Urgency_Present
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.8 KiB

No	827
Yes	155
	17

Length

Max length	3
Median length	2
Mean length	2.1211211
Min length	0

Characters and Unicode

Total characters	2119
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	Yes
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	827	82.8%
Yes	155	15.5%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	827	84.2%
yes	155	15.8%

Most occurring characters

Value	Count	Frequency (%)
N	827	39.0%
o	827	39.0%
Y	155	7.3%
e	155	7.3%
s	155	7.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2119	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	827	39.0%
o	827	39.0%
Y	155	7.3%
e	155	7.3%
s	155	7.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2119	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	827	39.0%
o	827	39.0%
Y	155	7.3%
e	155	7.3%
s	155	7.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2119	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	827	39.0%
o	827	39.0%
Y	155	7.3%
e	155	7.3%
s	155	7.3%

Temporal_Urgency_Words
Text

Distinct	107
Distinct (%)	10.7%
Missing	0
Missing (%)	0.0%
Memory size	59.4 KiB

Length

Max length	38
Median length	2
Mean length	3.7407407
Min length	0

Characters and Unicode

Total characters	3737
Distinct characters	55
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	86 ?
Unique (%)	8.6%

Sample

1st row	[]
2nd row	["begun"]
3rd row	[]
4th row	[]
5th row	[]

Value	Count	Frequency (%)
	827	77.6%
week	16	1.5%
now	14	1.3%
next	13	1.2%
this	11	1.0%
june	9	0.8%
immediately	6	0.6%
hours	6	0.6%
today	5	0.5%
before	5	0.5%
Other values (101)	154	14.4%

Most occurring characters

Value	Count	Frequency (%)
[	982	26.3%
]	982	26.3%
"	358	9.6%
e	167	4.5%
t	114	3.1%
n	101	2.7%
a	92	2.5%
	84	2.2%
o	82	2.2%
i	74	2.0%
Other values (45)	701	18.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3737	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	982	26.3%
]	982	26.3%
"	358	9.6%
e	167	4.5%
t	114	3.1%
n	101	2.7%
a	92	2.5%
	84	2.2%
o	82	2.2%
i	74	2.0%
Other values (45)	701	18.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3737	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	982	26.3%
]	982	26.3%
"	358	9.6%
e	167	4.5%
t	114	3.1%
n	101	2.7%
a	92	2.5%
	84	2.2%
o	82	2.2%
i	74	2.0%
Other values (45)	701	18.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3737	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	982	26.3%
]	982	26.3%
"	358	9.6%
e	167	4.5%
t	114	3.1%
n	101	2.7%
a	92	2.5%
	84	2.2%
o	82	2.2%
i	74	2.0%
Other values (45)	701	18.8%

Exclusivity_Present
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

No	942
Yes	40
	17

Length

Max length	3
Median length	2
Mean length	2.006006
Min length	0

Characters and Unicode

Total characters	2004
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	942	94.3%
Yes	40	4.0%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	942	95.9%
yes	40	4.1%

Most occurring characters

Value	Count	Frequency (%)
N	942	47.0%
o	942	47.0%
Y	40	2.0%
e	40	2.0%
s	40	2.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2004	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	942	47.0%
o	942	47.0%
Y	40	2.0%
e	40	2.0%
s	40	2.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2004	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	942	47.0%
o	942	47.0%
Y	40	2.0%
e	40	2.0%
s	40	2.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2004	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	942	47.0%
o	942	47.0%
Y	40	2.0%
e	40	2.0%
s	40	2.0%

Exclusivity_Words
Categorical

High correlation Imbalance

Distinct	33
Distinct (%)	3.3%
Missing	0
Missing (%)	0.0%
Memory size	58.1 KiB

[]	942
	17
["only"]	6
["unique"]	2
["smallest"]	2
Other values (28)	30

Length

Max length	39
Median length	2
Mean length	2.3723724
Min length	0

Characters and Unicode

Total characters	2370
Distinct characters	34
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	26 ?
Unique (%)	2.6%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	[]

Common Values

Value	Count	Frequency (%)
[]	942	94.3%
	17	1.7%
["only"]	6	0.6%
["unique"]	2	0.2%
["smallest"]	2	0.2%
["lesser-known"]	2	0.2%
["single"]	2	0.2%
["1 thing"]	1	0.1%
["last"]	1	0.1%
["sole"]	1	0.1%
Other values (23)	23	2.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	942	94.5%
only	6	0.6%
1	3	0.3%
first	3	0.3%
smallest	2	0.2%
lesser-known	2	0.2%
single	2	0.2%
unique	2	0.2%
one	2	0.2%
time	2	0.2%
Other values (30)	31	3.1%

Most occurring characters

Value	Count	Frequency (%)
[	982	41.4%
]	982	41.4%
"	84	3.5%
e	46	1.9%
s	29	1.2%
t	26	1.1%
n	24	1.0%
r	21	0.9%
i	21	0.9%
l	20	0.8%
Other values (24)	135	5.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2370	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	982	41.4%
]	982	41.4%
"	84	3.5%
e	46	1.9%
s	29	1.2%
t	26	1.1%
n	24	1.0%
r	21	0.9%
i	21	0.9%
l	20	0.8%
Other values (24)	135	5.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2370	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	982	41.4%
]	982	41.4%
"	84	3.5%
e	46	1.9%
s	29	1.2%
t	26	1.1%
n	24	1.0%
r	21	0.9%
i	21	0.9%
l	20	0.8%
Other values (24)	135	5.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2370	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	982	41.4%
]	982	41.4%
"	84	3.5%
e	46	1.9%
s	29	1.2%
t	26	1.1%
n	24	1.0%
r	21	0.9%
i	21	0.9%
l	20	0.8%
Other values (24)	135	5.7%

Authority_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.9 KiB

No	772
Yes	210
	17

Length

Max length	3
Median length	2
Mean length	2.1761762
Min length	0

Characters and Unicode

Total characters	2174
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	Yes
5th row	No

Common Values

Value	Count	Frequency (%)
No	772	77.3%
Yes	210	21.0%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	772	78.6%
yes	210	21.4%

Most occurring characters

Value	Count	Frequency (%)
N	772	35.5%
o	772	35.5%
Y	210	9.7%
e	210	9.7%
s	210	9.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2174	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	772	35.5%
o	772	35.5%
Y	210	9.7%
e	210	9.7%
s	210	9.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2174	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	772	35.5%
o	772	35.5%
Y	210	9.7%
e	210	9.7%
s	210	9.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2174	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	772	35.5%
o	772	35.5%
Y	210	9.7%
e	210	9.7%
s	210	9.7%

Authority_Words
Text

Distinct	140
Distinct (%)	14.0%
Missing	0
Missing (%)	0.0%
Memory size	60.3 KiB

Length

Max length	61
Median length	2
Mean length	4.6646647
Min length	0

Characters and Unicode

Total characters	4660
Distinct characters	56
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	109 ?
Unique (%)	10.9%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	["convicted"]
5th row	[]

Value	Count	Frequency (%)
	772	73.9%
confirms	15	1.4%
dwp	12	1.1%
hmrc	9	0.9%
experts	7	0.7%
told	6	0.6%
met	6	0.6%
office	5	0.5%
urged	5	0.5%
expert	4	0.4%
Other values (163)	203	19.4%

Most occurring characters

Value	Count	Frequency (%)
[	982	21.1%
]	982	21.1%
"	546	11.7%
e	220	4.7%
s	162	3.5%
r	157	3.4%
n	137	2.9%
i	136	2.9%
o	118	2.5%
a	118	2.5%
Other values (46)	1102	23.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4660	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	982	21.1%
]	982	21.1%
"	546	11.7%
e	220	4.7%
s	162	3.5%
r	157	3.4%
n	137	2.9%
i	136	2.9%
o	118	2.5%
a	118	2.5%
Other values (46)	1102	23.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4660	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	982	21.1%
]	982	21.1%
"	546	11.7%
e	220	4.7%
s	162	3.5%
r	157	3.4%
n	137	2.9%
i	136	2.9%
o	118	2.5%
a	118	2.5%
Other values (46)	1102	23.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4660	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	982	21.1%
]	982	21.1%
"	546	11.7%
e	220	4.7%
s	162	3.5%
r	157	3.4%
n	137	2.9%
i	136	2.9%
o	118	2.5%
a	118	2.5%
Other values (46)	1102	23.6%

Solution_Present
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.8 KiB

No	845
Yes	137
	17

Length

Max length	3
Median length	2
Mean length	2.1031031
Min length	0

Characters and Unicode

Total characters	2101
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	Yes
4th row	No
5th row	Yes

Common Values

Value	Count	Frequency (%)
No	845	84.6%
Yes	137	13.7%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	845	86.0%
yes	137	14.0%

Most occurring characters

Value	Count	Frequency (%)
N	845	40.2%
o	845	40.2%
Y	137	6.5%
e	137	6.5%
s	137	6.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2101	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	845	40.2%
o	845	40.2%
Y	137	6.5%
e	137	6.5%
s	137	6.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2101	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	845	40.2%
o	845	40.2%
Y	137	6.5%
e	137	6.5%
s	137	6.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2101	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	845	40.2%
o	845	40.2%
Y	137	6.5%
e	137	6.5%
s	137	6.5%

Solution_Words
Text

Distinct	128
Distinct (%)	12.8%
Missing	0
Missing (%)	0.0%
Memory size	60.2 KiB

Length

Max length	67
Median length	2
Mean length	4.3373373
Min length	0

Characters and Unicode

Total characters	4333
Distinct characters	49
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	117 ?
Unique (%)	11.7%

Sample

1st row	[]
2nd row	[]
3rd row	["best"]
4th row	[]
5th row	["smarter option","better"]

Value	Count	Frequency (%)
	845	76.0%
best	4	0.4%
ingredient	4	0.4%
item	4	0.4%
better	4	0.4%
put	3	0.3%
stay	3	0.3%
method	3	0.3%
to	3	0.3%
free	3	0.3%
Other values (210)	236	21.2%

Most occurring characters

Value	Count	Frequency (%)
[	982	22.7%
]	982	22.7%
"	386	8.9%
e	236	5.4%
t	184	4.2%
r	134	3.1%
	130	3.0%
i	122	2.8%
n	117	2.7%
s	115	2.7%
Other values (39)	945	21.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4333	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	982	22.7%
]	982	22.7%
"	386	8.9%
e	236	5.4%
t	184	4.2%
r	134	3.1%
	130	3.0%
i	122	2.8%
n	117	2.7%
s	115	2.7%
Other values (39)	945	21.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4333	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	982	22.7%
]	982	22.7%
"	386	8.9%
e	236	5.4%
t	184	4.2%
r	134	3.1%
	130	3.0%
i	122	2.8%
n	117	2.7%
s	115	2.7%
Other values (39)	945	21.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4333	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	982	22.7%
]	982	22.7%
"	386	8.9%
e	236	5.4%
t	184	4.2%
r	134	3.1%
	130	3.0%
i	122	2.8%
n	117	2.7%
s	115	2.7%
Other values (39)	945	21.8%

Economic_Benefit_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.8 KiB

No	791
Yes	191
	17

Length

Max length	3
Median length	2
Mean length	2.1571572
Min length	0

Characters and Unicode

Total characters	2155
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	791	79.2%
Yes	191	19.1%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	791	80.5%
yes	191	19.5%

Most occurring characters

Value	Count	Frequency (%)
N	791	36.7%
o	791	36.7%
Y	191	8.9%
e	191	8.9%
s	191	8.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2155	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	791	36.7%
o	791	36.7%
Y	191	8.9%
e	191	8.9%
s	191	8.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2155	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	791	36.7%
o	791	36.7%
Y	191	8.9%
e	191	8.9%
s	191	8.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2155	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	791	36.7%
o	791	36.7%
Y	191	8.9%
e	191	8.9%
s	191	8.9%

Economic_Benefit_Words
Text

Distinct	159
Distinct (%)	15.9%
Missing	0
Missing (%)	0.0%
Memory size	64.4 KiB

Length

Max length	56
Median length	2
Mean length	4.994995
Min length	0

Characters and Unicode

Total characters	4990
Distinct characters	62
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	139 ?
Unique (%)	13.9%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	[]

Value	Count	Frequency (%)
	791	74.1%
free	13	1.2%
payment	8	0.7%
payments	8	0.7%
of	7	0.7%
living	6	0.6%
fuel	5	0.5%
£300","payment	4	0.4%
cash	4	0.4%
cheap	4	0.4%
Other values (180)	218	20.4%

Most occurring characters

Value	Count	Frequency (%)
[	982	19.7%
]	982	19.7%
"	630	12.6%
e	231	4.6%
n	170	3.4%
a	151	3.0%
,	142	2.8%
s	131	2.6%
t	128	2.6%
i	120	2.4%
Other values (52)	1323	26.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4990	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	982	19.7%
]	982	19.7%
"	630	12.6%
e	231	4.6%
n	170	3.4%
a	151	3.0%
,	142	2.8%
s	131	2.6%
t	128	2.6%
i	120	2.4%
Other values (52)	1323	26.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4990	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	982	19.7%
]	982	19.7%
"	630	12.6%
e	231	4.6%
n	170	3.4%
a	151	3.0%
,	142	2.8%
s	131	2.6%
t	128	2.6%
i	120	2.4%
Other values (52)	1323	26.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4990	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	982	19.7%
]	982	19.7%
"	630	12.6%
e	231	4.6%
n	170	3.4%
a	151	3.0%
,	142	2.8%
s	131	2.6%
t	128	2.6%
i	120	2.4%
Other values (52)	1323	26.5%

Prohibition_Restriction_Present
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.7 KiB

No	891
Yes	91
	17

Length

Max length	3
Median length	2
Mean length	2.0570571
Min length	0

Characters and Unicode

Total characters	2055
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	891	89.2%
Yes	91	9.1%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	891	90.7%
yes	91	9.3%

Most occurring characters

Value	Count	Frequency (%)
N	891	43.4%
o	891	43.4%
Y	91	4.4%
e	91	4.4%
s	91	4.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2055	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	891	43.4%
o	891	43.4%
Y	91	4.4%
e	91	4.4%
s	91	4.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2055	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	891	43.4%
o	891	43.4%
Y	91	4.4%
e	91	4.4%
s	91	4.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2055	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	891	43.4%
o	891	43.4%
Y	91	4.4%
e	91	4.4%
s	91	4.4%

Prohibition_Restriction_Words
Text

Distinct	69
Distinct (%)	6.9%
Missing	0
Missing (%)	0.0%
Memory size	58.9 KiB

Length

Max length	47
Median length	2
Mean length	3.0950951
Min length	0

Characters and Unicode

Total characters	3092
Distinct characters	42
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	55 ?
Unique (%)	5.5%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	[]

Value	Count	Frequency (%)
	891	84.7%
not	9	0.9%
stop	7	0.7%
banned	6	0.6%
ban	6	0.6%
to	6	0.6%
rule	5	0.5%
no	3	0.3%
cancel	3	0.3%
fine	3	0.3%
Other values (93)	113	10.7%

Most occurring characters

Value	Count	Frequency (%)
[	982	31.8%
]	982	31.8%
"	210	6.8%
e	95	3.1%
n	87	2.8%
	70	2.3%
o	69	2.2%
i	60	1.9%
t	58	1.9%
a	55	1.8%
Other values (32)	424	13.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3092	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	982	31.8%
]	982	31.8%
"	210	6.8%
e	95	3.1%
n	87	2.8%
	70	2.3%
o	69	2.2%
i	60	1.9%
t	58	1.9%
a	55	1.8%
Other values (32)	424	13.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3092	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	982	31.8%
]	982	31.8%
"	210	6.8%
e	95	3.1%
n	87	2.8%
	70	2.3%
o	69	2.2%
i	60	1.9%
t	58	1.9%
a	55	1.8%
Other values (32)	424	13.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3092	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	982	31.8%
]	982	31.8%
"	210	6.8%
e	95	3.1%
n	87	2.8%
	70	2.3%
o	69	2.2%
i	60	1.9%
t	58	1.9%
a	55	1.8%
Other values (32)	424	13.7%

National_Relevance_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	58.1 KiB

No	546
Yes	436
	17

Length

Max length	3
Median length	2
Mean length	2.4024024
Min length	0

Characters and Unicode

Total characters	2400
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Yes
2nd row	Yes
3rd row	Yes
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	546	54.7%
Yes	436	43.6%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	546	55.6%
yes	436	44.4%

Most occurring characters

Value	Count	Frequency (%)
N	546	22.8%
o	546	22.8%
Y	436	18.2%
e	436	18.2%
s	436	18.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2400	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	546	22.8%
o	546	22.8%
Y	436	18.2%
e	436	18.2%
s	436	18.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2400	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	546	22.8%
o	546	22.8%
Y	436	18.2%
e	436	18.2%
s	436	18.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2400	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	546	22.8%
o	546	22.8%
Y	436	18.2%
e	436	18.2%
s	436	18.2%

National_Relevance_Words
Text

Distinct	211
Distinct (%)	21.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

Length

Max length	91
Median length	2
Mean length	7.1031031
Min length	0

Characters and Unicode

Total characters	7096
Distinct characters	60
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	167 ?
Unique (%)	16.7%

Sample

1st row	["British","Russian"]
2nd row	["England"]
3rd row	["English","London"]
4th row	[]
5th row	[]

Value	Count	Frequency (%)
	546	51.9%
uk	101	9.6%
england	45	4.3%
london	16	1.5%
dwp	9	0.9%
manchester	8	0.8%
british	7	0.7%
hmrc	7	0.7%
britain	6	0.6%
households	5	0.5%
Other values (230)	303	28.8%

Most occurring characters

Value	Count	Frequency (%)
"	1204	17.0%
[	982	13.8%
]	982	13.8%
n	410	5.8%
a	279	3.9%
r	223	3.1%
e	214	3.0%
i	212	3.0%
s	203	2.9%
o	203	2.9%
Other values (50)	2184	30.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7096	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
"	1204	17.0%
[	982	13.8%
]	982	13.8%
n	410	5.8%
a	279	3.9%
r	223	3.1%
e	214	3.0%
i	212	3.0%
s	203	2.9%
o	203	2.9%
Other values (50)	2184	30.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7096	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
"	1204	17.0%
[	982	13.8%
]	982	13.8%
n	410	5.8%
a	279	3.9%
r	223	3.1%
e	214	3.0%
i	212	3.0%
s	203	2.9%
o	203	2.9%
Other values (50)	2184	30.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7096	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
"	1204	17.0%
[	982	13.8%
]	982	13.8%
n	410	5.8%
a	279	3.9%
r	223	3.1%
e	214	3.0%
i	212	3.0%
s	203	2.9%
o	203	2.9%
Other values (50)	2184	30.8%

Recognized_Brand_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	58.0 KiB

No	641
Yes	341
	17

Length

Max length	3
Median length	2
Mean length	2.3073073
Min length	0

Characters and Unicode

Total characters	2305
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	Yes

Common Values

Value	Count	Frequency (%)
No	641	64.2%
Yes	341	34.1%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	641	65.3%
yes	341	34.7%

Most occurring characters

Value	Count	Frequency (%)
N	641	27.8%
o	641	27.8%
Y	341	14.8%
e	341	14.8%
s	341	14.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2305	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	641	27.8%
o	641	27.8%
Y	341	14.8%
e	341	14.8%
s	341	14.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2305	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	641	27.8%
o	641	27.8%
Y	341	14.8%
e	341	14.8%
s	341	14.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2305	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	641	27.8%
o	641	27.8%
Y	341	14.8%
e	341	14.8%
s	341	14.8%

Recognized_Brand_Words
Text

Distinct	232
Distinct (%)	23.2%
Missing	0
Missing (%)	0.0%
Memory size	63.2 KiB

Length

Max length	65
Median length	2
Mean length	7.3883884
Min length	0

Characters and Unicode

Total characters	7381
Distinct characters	69
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	194 ?
Unique (%)	19.4%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	["Tesco"]

Value	Count	Frequency (%)
	641	53.6%
dwp	26	2.2%
air	12	1.0%
hmrc	11	0.9%
india	9	0.8%
glastonbury	7	0.6%
the	6	0.5%
bbc	6	0.5%
british	6	0.5%
aldi	6	0.5%
Other values (348)	465	38.9%

Most occurring characters

Value	Count	Frequency (%)
"	1004	13.6%
[	982	13.3%
]	982	13.3%
a	361	4.9%
e	307	4.2%
r	276	3.7%
n	255	3.5%
i	253	3.4%
s	214	2.9%
	213	2.9%
Other values (59)	2534	34.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7381	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
"	1004	13.6%
[	982	13.3%
]	982	13.3%
a	361	4.9%
e	307	4.2%
r	276	3.7%
n	255	3.5%
i	253	3.4%
s	214	2.9%
	213	2.9%
Other values (59)	2534	34.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7381	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
"	1004	13.6%
[	982	13.3%
]	982	13.3%
a	361	4.9%
e	307	4.2%
r	276	3.7%
n	255	3.5%
i	253	3.4%
s	214	2.9%
	213	2.9%
Other values (59)	2534	34.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7381	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
"	1004	13.6%
[	982	13.3%
]	982	13.3%
a	361	4.9%
e	307	4.2%
r	276	3.7%
n	255	3.5%
i	253	3.4%
s	214	2.9%
	213	2.9%
Other values (59)	2534	34.3%

Curiosity_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	58.4 KiB

Yes	750
No	232
	17

Length

Max length	3
Median length	3
Mean length	2.7167167
Min length	0

Characters and Unicode

Total characters	2714
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	Yes
3rd row	Yes
4th row	Yes
5th row	Yes

Common Values

Value	Count	Frequency (%)
Yes	750	75.1%
No	232	23.2%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
yes	750	76.4%
no	232	23.6%

Most occurring characters

Value	Count	Frequency (%)
Y	750	27.6%
e	750	27.6%
s	750	27.6%
N	232	8.5%
o	232	8.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2714	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
Y	750	27.6%
e	750	27.6%
s	750	27.6%
N	232	8.5%
o	232	8.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2714	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
Y	750	27.6%
e	750	27.6%
s	750	27.6%
N	232	8.5%
o	232	8.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2714	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
Y	750	27.6%
e	750	27.6%
s	750	27.6%
N	232	8.5%
o	232	8.5%

Curiosity_Evidence
Text

Distinct	754
Distinct (%)	75.5%
Missing	0
Missing (%)	0.0%
Memory size	163.0 KiB

Length

Max length	249
Median length	194
Mean length	100.38138
Min length	0

Characters and Unicode

Total characters	100281
Distinct characters	87
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	753 ?
Unique (%)	75.4%

Sample

1st row
2nd row	The headline creates an information gap by mentioning a 'new driveway rule change' without specifying what the change is, prompting the reader to click to find out.
3rd row	The headline creates curiosity by promising the "best day trip" from London without immediately revealing the city.
4th row	The unusual act of 'covering road with potatoes and silt' creates a strong information gap and makes the reader want to know the backstory.
5th row	The phrase "smarter option that covers your entire outdoor space better" creates an information gap, prompting the reader to discover what this new solution is.

Value	Count	Frequency (%)
the	1745	10.8%
and	538	3.3%
to	536	3.3%
creates	496	3.1%
information	492	3.0%
gap	479	3.0%
an	468	2.9%
about	386	2.4%
phrase	331	2.0%
of	298	1.8%
Other values (2201)	10378	64.3%

Most occurring characters

Value	Count	Frequency (%)
	15396	15.4%
e	9733	9.7%
a	7503	7.5%
t	7327	7.3%
i	6420	6.4%
n	6050	6.0%
r	5685	5.7%
o	5563	5.5%
s	4914	4.9%
h	3972	4.0%
Other values (77)	27718	27.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	100281	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	15396	15.4%
e	9733	9.7%
a	7503	7.5%
t	7327	7.3%
i	6420	6.4%
n	6050	6.0%
r	5685	5.7%
o	5563	5.5%
s	4914	4.9%
h	3972	4.0%
Other values (77)	27718	27.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	100281	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	15396	15.4%
e	9733	9.7%
a	7503	7.5%
t	7327	7.3%
i	6420	6.4%
n	6050	6.0%
r	5685	5.7%
o	5563	5.5%
s	4914	4.9%
h	3972	4.0%
Other values (77)	27718	27.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	100281	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	15396	15.4%
e	9733	9.7%
a	7503	7.5%
t	7327	7.3%
i	6420	6.4%
n	6050	6.0%
r	5685	5.7%
o	5563	5.5%
s	4914	4.9%
h	3972	4.0%
Other values (77)	27718	27.6%

Fear_Concern_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	58.1 KiB

No	519
Yes	463
	17

Length

Max length	3
Median length	2
Mean length	2.4294294
Min length	0

Characters and Unicode

Total characters	2427
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Yes
2nd row	Yes
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	519	52.0%
Yes	463	46.3%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	519	52.9%
yes	463	47.1%

Most occurring characters

Value	Count	Frequency (%)
N	519	21.4%
o	519	21.4%
Y	463	19.1%
e	463	19.1%
s	463	19.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2427	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	519	21.4%
o	519	21.4%
Y	463	19.1%
e	463	19.1%
s	463	19.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2427	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	519	21.4%
o	519	21.4%
Y	463	19.1%
e	463	19.1%
s	463	19.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2427	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	519	21.4%
o	519	21.4%
Y	463	19.1%
e	463	19.1%
s	463	19.1%

Fear_Concern_Evidence
Text

Distinct	469
Distinct (%)	46.9%
Missing	0
Missing (%)	0.0%
Memory size	116.5 KiB

Length

Max length	227
Median length	0
Mean length	56.201201
Min length	0

Characters and Unicode

Total characters	56145
Distinct characters	78
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	468 ?
Unique (%)	46.8%

Sample

1st row	The mention of 'intercept' and 'military aircraft' implies a potential threat or escalating tensions.
2nd row	The phrase 'affecting every home' can generate concern or fear among homeowners about potential negative consequences or obligations.
3rd row
4th row
5th row

Value	Count	Frequency (%)
the	575	6.8%
concern	384	4.5%
and	380	4.5%
of	297	3.5%
a	289	3.4%
or	206	2.4%
potential	173	2.0%
for	172	2.0%
about	167	2.0%
to	139	1.6%
Other values (1621)	5683	67.1%

Most occurring characters

Value	Count	Frequency (%)
	7997	14.2%
e	5962	10.6%
n	4153	7.4%
a	3661	6.5%
o	3634	6.5%
t	3459	6.2%
i	3275	5.8%
r	3177	5.7%
s	2721	4.8%
c	2383	4.2%
Other values (68)	15723	28.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	56145	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	7997	14.2%
e	5962	10.6%
n	4153	7.4%
a	3661	6.5%
o	3634	6.5%
t	3459	6.2%
i	3275	5.8%
r	3177	5.7%
s	2721	4.8%
c	2383	4.2%
Other values (68)	15723	28.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	56145	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	7997	14.2%
e	5962	10.6%
n	4153	7.4%
a	3661	6.5%
o	3634	6.5%
t	3459	6.2%
i	3275	5.8%
r	3177	5.7%
s	2721	4.8%
c	2383	4.2%
Other values (68)	15723	28.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	56145	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	7997	14.2%
e	5962	10.6%
n	4153	7.4%
a	3661	6.5%
o	3634	6.5%
t	3459	6.2%
i	3275	5.8%
r	3177	5.7%
s	2721	4.8%
c	2383	4.2%
Other values (68)	15723	28.0%

Surprise_Awe_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.9 KiB

No	732
Yes	250
	17

Length

Max length	3
Median length	2
Mean length	2.2162162
Min length	0

Characters and Unicode

Total characters	2214
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	Yes
5th row	No

Common Values

Value	Count	Frequency (%)
No	732	73.3%
Yes	250	25.0%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	732	74.5%
yes	250	25.5%

Most occurring characters

Value	Count	Frequency (%)
N	732	33.1%
o	732	33.1%
Y	250	11.3%
e	250	11.3%
s	250	11.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2214	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	732	33.1%
o	732	33.1%
Y	250	11.3%
e	250	11.3%
s	250	11.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2214	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	732	33.1%
o	732	33.1%
Y	250	11.3%
e	250	11.3%
s	250	11.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2214	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	732	33.1%
o	732	33.1%
Y	250	11.3%
e	250	11.3%
s	250	11.3%

Surprise_Awe_Evidence
Text

Distinct	255
Distinct (%)	25.5%
Missing	0
Missing (%)	0.0%
Memory size	87.1 KiB

Length

Max length	184
Median length	0
Mean length	27.762763
Min length	0

Characters and Unicode

Total characters	27735
Distinct characters	80
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	254 ?
Unique (%)	25.4%

Sample

1st row
2nd row
3rd row
4th row	The combination of 'potatoes and silt' as a method for a crime is unexpected and bizarre.
5th row

Value	Count	Frequency (%)
the	363	8.1%
of	262	5.8%
a	257	5.7%
and	197	4.4%
surprise	133	3.0%
unexpected	100	2.2%
is	94	2.1%
can	83	1.8%
surprising	73	1.6%
evoke	69	1.5%
Other values (1219)	2865	63.7%

Most occurring characters

Value	Count	Frequency (%)
	4243	15.3%
e	3037	11.0%
n	1830	6.6%
i	1757	6.3%
a	1734	6.3%
s	1677	6.0%
t	1519	5.5%
r	1442	5.2%
o	1385	5.0%
c	825	3.0%
Other values (70)	8286	29.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	27735	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	4243	15.3%
e	3037	11.0%
n	1830	6.6%
i	1757	6.3%
a	1734	6.3%
s	1677	6.0%
t	1519	5.5%
r	1442	5.2%
o	1385	5.0%
c	825	3.0%
Other values (70)	8286	29.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	27735	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	4243	15.3%
e	3037	11.0%
n	1830	6.6%
i	1757	6.3%
a	1734	6.3%
s	1677	6.0%
t	1519	5.5%
r	1442	5.2%
o	1385	5.0%
c	825	3.0%
Other values (70)	8286	29.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	27735	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	4243	15.3%
e	3037	11.0%
n	1830	6.6%
i	1757	6.3%
a	1734	6.3%
s	1677	6.0%
t	1519	5.5%
r	1442	5.2%
o	1385	5.0%
c	825	3.0%
Other values (70)	8286	29.9%

Indignation_Controversy_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	57.8 KiB

No	801
Yes	181
	17

Length

Max length	3
Median length	2
Mean length	2.1471471
Min length	0

Characters and Unicode

Total characters	2145
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	801	80.2%
Yes	181	18.1%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	801	81.6%
yes	181	18.4%

Most occurring characters

Value	Count	Frequency (%)
N	801	37.3%
o	801	37.3%
Y	181	8.4%
e	181	8.4%
s	181	8.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2145	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	801	37.3%
o	801	37.3%
Y	181	8.4%
e	181	8.4%
s	181	8.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2145	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	801	37.3%
o	801	37.3%
Y	181	8.4%
e	181	8.4%
s	181	8.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2145	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	801	37.3%
o	801	37.3%
Y	181	8.4%
e	181	8.4%
s	181	8.4%

Indignation_Controversy_Evidence
Text

Distinct	188
Distinct (%)	18.8%
Missing	0
Missing (%)	0.0%
Memory size	80.6 KiB

Length

Max length	242
Median length	0
Mean length	23.992993
Min length	0

Characters and Unicode

Total characters	23969
Distinct characters	69
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	187 ?
Unique (%)	18.7%

Sample

1st row
2nd row
3rd row
4th row
5th row

Value	Count	Frequency (%)
the	250	7.0%
and	161	4.5%
of	128	3.6%
indignation	119	3.3%
a	117	3.3%
or	115	3.2%
debate	101	2.8%
to	93	2.6%
provoke	71	2.0%
can	68	1.9%
Other values (974)	2361	65.9%

Most occurring characters

Value	Count	Frequency (%)
	3397	14.2%
e	2205	9.2%
n	1859	7.8%
i	1771	7.4%
o	1725	7.2%
a	1698	7.1%
t	1604	6.7%
r	1228	5.1%
s	1073	4.5%
d	806	3.4%
Other values (59)	6603	27.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	23969	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	3397	14.2%
e	2205	9.2%
n	1859	7.8%
i	1771	7.4%
o	1725	7.2%
a	1698	7.1%
t	1604	6.7%
r	1228	5.1%
s	1073	4.5%
d	806	3.4%
Other values (59)	6603	27.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	23969	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	3397	14.2%
e	2205	9.2%
n	1859	7.8%
i	1771	7.4%
o	1725	7.2%
a	1698	7.1%
t	1604	6.7%
r	1228	5.1%
s	1073	4.5%
d	806	3.4%
Other values (59)	6603	27.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	23969	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	3397	14.2%
e	2205	9.2%
n	1859	7.8%
i	1771	7.4%
o	1725	7.2%
a	1698	7.1%
t	1604	6.7%
r	1228	5.1%
s	1073	4.5%
d	806	3.4%
Other values (59)	6603	27.5%

Hope_Optimism_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	58.0 KiB

No	659
Yes	323
	17

Length

Max length	3
Median length	2
Mean length	2.2892893
Min length	0

Characters and Unicode

Total characters	2287
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	No
3rd row	Yes
4th row	No
5th row	Yes

Common Values

Value	Count	Frequency (%)
No	659	66.0%
Yes	323	32.3%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	659	67.1%
yes	323	32.9%

Most occurring characters

Value	Count	Frequency (%)
N	659	28.8%
o	659	28.8%
Y	323	14.1%
e	323	14.1%
s	323	14.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2287	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	659	28.8%
o	659	28.8%
Y	323	14.1%
e	323	14.1%
s	323	14.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2287	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	659	28.8%
o	659	28.8%
Y	323	14.1%
e	323	14.1%
s	323	14.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2287	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	659	28.8%
o	659	28.8%
Y	323	14.1%
e	323	14.1%
s	323	14.1%

Hope_Optimism_Evidence
Text

Distinct	328
Distinct (%)	32.8%
Missing	0
Missing (%)	0.0%
Memory size	94.6 KiB

Length

Max length	217
Median length	0
Mean length	36.078078
Min length	0

Characters and Unicode

Total characters	36042
Distinct characters	77
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	327 ?
Unique (%)	32.7%

Sample

1st row
2nd row
3rd row	The phrase "best day trip" evokes a sense of positive experience and an ideal outcome for readers seeking a trip.
4th row
5th row	The headline offers a "smarter option" that performs "better," suggesting an improved solution to a common outdoor challenge, thereby instilling hope for a more effective product.

Value	Count	Frequency (%)
a	455	8.1%
the	359	6.4%
and	262	4.7%
for	228	4.1%
of	214	3.8%
positive	210	3.8%
hope	147	2.6%
to	121	2.2%
offers	106	1.9%
outcome	70	1.3%
Other values (1157)	3416	61.1%

Most occurring characters

Value	Count	Frequency (%)
	5262	14.6%
e	3963	11.0%
o	2735	7.6%
i	2426	6.7%
t	2125	5.9%
s	2110	5.9%
a	2086	5.8%
n	2051	5.7%
r	1735	4.8%
p	1140	3.2%
Other values (67)	10409	28.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	36042	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	5262	14.6%
e	3963	11.0%
o	2735	7.6%
i	2426	6.7%
t	2125	5.9%
s	2110	5.9%
a	2086	5.8%
n	2051	5.7%
r	1735	4.8%
p	1140	3.2%
Other values (67)	10409	28.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	36042	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	5262	14.6%
e	3963	11.0%
o	2735	7.6%
i	2426	6.7%
t	2125	5.9%
s	2110	5.9%
a	2086	5.8%
n	2051	5.7%
r	1735	4.8%
p	1140	3.2%
Other values (67)	10409	28.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	36042	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	5262	14.6%
e	3963	11.0%
o	2735	7.6%
i	2426	6.7%
t	2125	5.9%
s	2110	5.9%
a	2086	5.8%
n	2051	5.7%
r	1735	4.8%
p	1140	3.2%
Other values (67)	10409	28.9%

Personal_Identification_Present
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	58.4 KiB

Yes	780
No	202
	17

Length

Max length	3
Median length	3
Mean length	2.7467467
Min length	0

Characters and Unicode

Total characters	2744
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	No
2nd row	Yes
3rd row	Yes
4th row	No
5th row	Yes

Common Values

Value	Count	Frequency (%)
Yes	780	78.1%
No	202	20.2%
	17	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
yes	780	79.4%
no	202	20.6%

Most occurring characters

Value	Count	Frequency (%)
Y	780	28.4%
e	780	28.4%
s	780	28.4%
N	202	7.4%
o	202	7.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2744	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
Y	780	28.4%
e	780	28.4%
s	780	28.4%
N	202	7.4%
o	202	7.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2744	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
Y	780	28.4%
e	780	28.4%
s	780	28.4%
N	202	7.4%
o	202	7.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2744	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
Y	780	28.4%
e	780	28.4%
s	780	28.4%
N	202	7.4%
o	202	7.4%

Personal_Identification_Evidence
Text

Distinct	781
Distinct (%)	78.2%
Missing	0
Missing (%)	0.0%
Memory size	150.7 KiB

Length

Max length	258
Median length	178
Mean length	95.17017
Min length	0

Characters and Unicode

Total characters	95075
Distinct characters	80
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	779 ?
Unique (%)	78.0%

Sample

1st row
2nd row	Directly appeals to residents of 'England' and specifically to those who are homeowners ('every home').
3rd row	The headline directly appeals to anyone interested in day trips from London, allowing them to easily identify with the topic.
4th row
5th row	The phrase "Say goodbye to parasols" and reference to "your entire outdoor space" directly addresses the reader, implying a common problem they might face and offering a relevant solution.

Value	Count	Frequency (%)
the	1034	7.1%
to	621	4.3%
of	480	3.3%
and	445	3.1%
directly	414	2.9%
with	393	2.7%
a	372	2.6%
or	321	2.2%
identify	262	1.8%
who	233	1.6%
Other values (1801)	9907	68.4%

Most occurring characters

Value	Count	Frequency (%)
	13702	14.4%
e	10277	10.8%
i	6663	7.0%
t	6404	6.7%
a	6136	6.5%
n	5746	6.0%
o	5303	5.6%
s	5079	5.3%
r	5058	5.3%
l	3908	4.1%
Other values (70)	26799	28.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	95075	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	13702	14.4%
e	10277	10.8%
i	6663	7.0%
t	6404	6.7%
a	6136	6.5%
n	5746	6.0%
o	5303	5.6%
s	5079	5.3%
r	5058	5.3%
l	3908	4.1%
Other values (70)	26799	28.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	95075	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	13702	14.4%
e	10277	10.8%
i	6663	7.0%
t	6404	6.7%
a	6136	6.5%
n	5746	6.0%
o	5303	5.6%
s	5079	5.3%
r	5058	5.3%
l	3908	4.1%
Other values (70)	26799	28.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	95075	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	13702	14.4%
e	10277	10.8%
i	6663	7.0%
t	6404	6.7%
a	6136	6.5%
n	5746	6.0%
o	5303	5.6%
s	5079	5.3%
r	5058	5.3%
l	3908	4.1%
Other values (70)	26799	28.2%

Interactions

Correlations

	Authority_Present	Clarity_and_Conciseness_Value	Contains_Colon	Contains_Exclamation_Mark	Contains_Hyphen	Contains_Numbers	Contains_Question_Mark	Contains_Quotes	Curiosity_Present	Economic_Benefit_Present	Emphatic_Capitalization_Usage	Ends_With_Question_Mark	Exclusivity_Present	Exclusivity_Words	Fear_Concern_Present	Hope_Optimism_Present	Indignation_Controversy_Present	Length_General_Assessment	Main_Category	Main_Classification	National_Relevance_Present	Originality_and_Differentiation_Value	Personal_Identification_Present	Prohibition_Restriction_Present	Recognized_Brand_Present	Relevance_and_Timeliness_Value	Solution_Present	Starts_With_Number	Strategic_Keyword_Usage_Value	Surprise_Awe_Present	Temporal_Urgency_Present	Visibility
Authority_Present	1.000	0.706	0.706	0.706	0.707	0.707	0.706	0.706	0.706	0.710	0.699	0.706	0.707	0.695	0.707	0.707	0.707	0.707	0.719	0.737	0.707	0.708	0.708	0.708	0.712	0.709	0.710	0.706	0.709	0.707	0.706	1.000
Clarity_and_Conciseness_Value	0.706	1.000	0.708	0.706	0.706	0.707	0.706	0.711	0.707	0.706	0.563	0.706	0.706	0.550	0.708	0.706	0.716	0.838	0.585	0.567	0.706	0.584	0.707	0.706	0.706	0.579	0.707	0.706	0.577	0.706	0.707	1.000
Contains_Colon	0.706	0.708	1.000	0.712	0.707	0.706	0.708	0.712	0.707	0.708	0.718	0.708	0.707	0.691	0.708	0.708	0.707	0.713	0.700	0.742	0.706	0.706	0.706	0.709	0.707	0.706	0.707	0.707	0.707	0.706	0.706	1.000
Contains_Exclamation_Mark	0.706	0.706	0.712	1.000	0.706	0.707	0.706	0.708	0.707	0.706	0.690	0.706	0.706	0.685	0.707	0.707	0.706	0.706	0.704	0.703	0.707	0.706	0.706	0.710	0.707	0.706	0.706	0.706	0.706	0.707	0.708	1.000
Contains_Hyphen	0.707	0.706	0.707	0.706	1.000	0.711	0.707	0.707	0.715	0.706	0.707	0.707	0.707	0.699	0.708	0.708	0.706	0.711	0.702	0.707	0.706	0.712	0.707	0.706	0.708	0.706	0.708	0.708	0.707	0.708	0.706	1.000
Contains_Numbers	0.707	0.707	0.706	0.707	0.711	1.000	0.707	0.713	0.707	0.734	0.700	0.707	0.707	0.697	0.707	0.716	0.709	0.707	0.719	0.728	0.706	0.709	0.715	0.707	0.707	0.709	0.711	0.719	0.709	0.707	0.707	1.000
Contains_Question_Mark	0.706	0.706	0.708	0.706	0.707	0.707	1.000	0.707	0.708	0.707	0.719	0.942	0.706	0.688	0.707	0.707	0.707	0.707	0.706	0.964	0.706	0.706	0.706	0.706	0.707	0.706	0.706	0.707	0.706	0.708	0.708	1.000
Contains_Quotes	0.706	0.711	0.712	0.708	0.707	0.713	0.707	1.000	0.709	0.707	0.699	0.708	0.707	0.699	0.709	0.707	0.711	0.709	0.709	0.776	0.708	0.712	0.707	0.706	0.707	0.706	0.706	0.708	0.706	0.707	0.706	1.000
Curiosity_Present	0.706	0.707	0.707	0.707	0.715	0.707	0.708	0.709	1.000	0.707	0.698	0.708	0.707	0.694	0.718	0.710	0.710	0.706	0.735	0.727	0.708	0.740	0.706	0.707	0.707	0.706	0.710	0.707	0.711	0.720	0.707	1.000
Economic_Benefit_Present	0.710	0.706	0.708	0.706	0.706	0.734	0.707	0.707	0.707	1.000	0.701	0.707	0.709	0.706	0.711	0.729	0.706	0.707	0.788	0.704	0.708	0.709	0.717	0.707	0.710	0.708	0.707	0.706	0.709	0.707	0.708	1.000
Emphatic_Capitalization_Usage	0.699	0.563	0.718	0.690	0.707	0.700	0.719	0.699	0.698	0.701	1.000	0.702	0.703	0.229	0.699	0.699	0.698	0.703	0.229	0.226	0.701	0.566	0.695	0.698	0.699	0.559	0.696	0.690	0.557	0.700	0.705	1.000
Ends_With_Question_Mark	0.706	0.706	0.708	0.706	0.707	0.707	0.942	0.708	0.708	0.707	0.702	1.000	0.707	0.689	0.707	0.706	0.707	0.707	0.703	0.956	0.706	0.706	0.706	0.707	0.706	0.706	0.707	0.707	0.706	0.707	0.707	1.000
Exclusivity_Present	0.707	0.706	0.707	0.706	0.707	0.707	0.706	0.707	0.707	0.709	0.703	0.707	1.000	0.985	0.707	0.711	0.706	0.706	0.704	0.702	0.707	0.711	0.706	0.706	0.707	0.706	0.708	0.707	0.707	0.709	0.707	1.000
Exclusivity_Words	0.695	0.550	0.691	0.685	0.699	0.697	0.688	0.699	0.694	0.706	0.229	0.689	0.985	1.000	0.696	0.702	0.694	0.698	0.249	0.190	0.697	0.568	0.694	0.701	0.698	0.566	0.705	0.685	0.551	0.702	0.697	1.000
Fear_Concern_Present	0.707	0.708	0.708	0.707	0.708	0.707	0.707	0.709	0.718	0.711	0.699	0.707	0.707	0.696	1.000	0.764	0.730	0.708	0.782	0.726	0.708	0.709	0.713	0.723	0.707	0.707	0.710	0.706	0.706	0.715	0.721	1.000
Hope_Optimism_Present	0.707	0.706	0.708	0.707	0.708	0.716	0.707	0.707	0.710	0.729	0.699	0.706	0.711	0.702	0.764	1.000	0.727	0.706	0.775	0.727	0.708	0.711	0.721	0.711	0.711	0.706	0.786	0.707	0.706	0.707	0.709	1.000
Indignation_Controversy_Present	0.707	0.716	0.707	0.706	0.706	0.709	0.707	0.711	0.710	0.706	0.698	0.707	0.706	0.694	0.730	0.727	1.000	0.715	0.731	0.709	0.707	0.712	0.709	0.718	0.706	0.706	0.711	0.706	0.706	0.711	0.708	1.000
Length_General_Assessment	0.707	0.838	0.713	0.706	0.711	0.707	0.707	0.709	0.706	0.707	0.703	0.707	0.706	0.698	0.708	0.706	0.715	1.000	0.713	0.704	0.706	0.714	0.707	0.707	0.706	0.708	0.706	0.707	0.706	0.707	0.708	1.000
Main_Category	0.719	0.585	0.700	0.704	0.702	0.719	0.706	0.709	0.735	0.788	0.229	0.703	0.704	0.249	0.782	0.775	0.731	0.713	1.000	0.304	0.758	0.600	0.771	0.715	0.758	0.579	0.822	0.706	0.578	0.732	0.720	1.000
Main_Classification	0.737	0.567	0.742	0.703	0.707	0.728	0.964	0.776	0.727	0.704	0.226	0.956	0.702	0.190	0.726	0.727	0.709	0.704	0.304	1.000	0.712	0.583	0.703	0.697	0.711	0.565	0.738	0.739	0.561	0.703	0.723	1.000
National_Relevance_Present	0.707	0.706	0.706	0.707	0.706	0.706	0.706	0.708	0.708	0.708	0.701	0.706	0.707	0.697	0.708	0.708	0.707	0.706	0.758	0.712	1.000	0.706	0.707	0.707	0.707	0.706	0.717	0.707	0.709	0.706	0.708	1.000
Originality_and_Differentiation_Value	0.708	0.584	0.706	0.706	0.712	0.709	0.706	0.712	0.740	0.709	0.566	0.706	0.711	0.568	0.709	0.711	0.712	0.714	0.600	0.583	0.706	1.000	0.713	0.706	0.706	0.598	0.709	0.707	0.596	0.759	0.709	1.000
Personal_Identification_Present	0.708	0.707	0.706	0.706	0.707	0.715	0.706	0.707	0.706	0.717	0.695	0.706	0.706	0.694	0.713	0.721	0.709	0.707	0.771	0.703	0.707	0.713	1.000	0.708	0.707	0.707	0.715	0.707	0.709	0.722	0.712	1.000
Prohibition_Restriction_Present	0.708	0.706	0.709	0.710	0.706	0.707	0.706	0.706	0.707	0.707	0.698	0.707	0.706	0.701	0.723	0.711	0.718	0.707	0.715	0.697	0.707	0.706	0.708	1.000	0.706	0.710	0.706	0.707	0.707	0.706	0.707	1.000
Recognized_Brand_Present	0.712	0.706	0.707	0.707	0.708	0.707	0.707	0.707	0.707	0.710	0.699	0.706	0.707	0.698	0.707	0.711	0.706	0.706	0.758	0.711	0.707	0.706	0.707	0.706	1.000	0.707	0.713	0.708	0.711	0.709	0.706	1.000
Relevance_and_Timeliness_Value	0.709	0.579	0.706	0.706	0.706	0.709	0.706	0.706	0.706	0.708	0.559	0.706	0.706	0.566	0.707	0.706	0.706	0.708	0.579	0.565	0.706	0.598	0.707	0.710	0.707	1.000	0.707	0.707	0.726	0.708	0.707	1.000
Solution_Present	0.710	0.707	0.707	0.706	0.708	0.711	0.706	0.706	0.710	0.707	0.696	0.707	0.708	0.705	0.710	0.786	0.711	0.706	0.822	0.738	0.717	0.709	0.715	0.706	0.713	0.707	1.000	0.707	0.706	0.708	0.706	1.000
Starts_With_Number	0.706	0.706	0.707	0.706	0.708	0.719	0.707	0.708	0.707	0.706	0.690	0.707	0.707	0.685	0.706	0.707	0.706	0.707	0.706	0.739	0.707	0.707	0.707	0.707	0.708	0.707	0.707	1.000	0.706	0.707	0.706	1.000
Strategic_Keyword_Usage_Value	0.709	0.577	0.707	0.706	0.707	0.709	0.706	0.706	0.711	0.709	0.557	0.706	0.707	0.551	0.706	0.706	0.706	0.706	0.578	0.561	0.709	0.596	0.709	0.707	0.711	0.726	0.706	0.706	1.000	0.708	0.706	1.000
Surprise_Awe_Present	0.707	0.706	0.706	0.707	0.708	0.707	0.708	0.707	0.720	0.707	0.700	0.707	0.709	0.702	0.715	0.707	0.711	0.707	0.732	0.703	0.706	0.759	0.722	0.706	0.709	0.708	0.708	0.707	0.708	1.000	0.707	1.000
Temporal_Urgency_Present	0.706	0.707	0.706	0.708	0.706	0.707	0.708	0.706	0.707	0.708	0.705	0.707	0.707	0.697	0.721	0.709	0.708	0.708	0.720	0.723	0.708	0.709	0.712	0.707	0.706	0.707	0.706	0.706	0.706	0.707	1.000	1.000
Visibility	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

	Title	Visibility	Cleaned_Headline	Main_Category	Subcategory_1	Subcategory_2	Clarity_and_Conciseness_Value	Clarity_and_Conciseness_Comment	Relevance_and_Timeliness_Value	Relevance_and_Timeliness_Comment	Strategic_Keyword_Usage_Value	Strategic_Keyword_Usage_Comment	Originality_and_Differentiation_Value	Originality_and_Differentiation_Comment	Contains_Numbers	Contains_Quotes	Contains_Question_Mark	Contains_Colon	Contains_Hyphen	Contains_Exclamation_Mark	Starts_With_Number	Ends_With_Question_Mark	Length_General_Assessment	Length_Number_of_Characters	Emphatic_Capitalization_Usage	Main_Classification	Comment_Type_Justification	Temporal_Urgency_Present	Temporal_Urgency_Words	Exclusivity_Present	Exclusivity_Words	Authority_Present	Authority_Words	Solution_Present	Solution_Words	Economic_Benefit_Present	Economic_Benefit_Words	Prohibition_Restriction_Present	Prohibition_Restriction_Words	National_Relevance_Present	National_Relevance_Words	Recognized_Brand_Present	Recognized_Brand_Words	Curiosity_Present	Curiosity_Evidence	Fear_Concern_Present	Fear_Concern_Evidence	Surprise_Awe_Present	Surprise_Awe_Evidence	Indignation_Controversy_Present	Indignation_Controversy_Evidence	Hope_Optimism_Present	Hope_Optimism_Evidence	Personal_Identification_Present	Personal_Identification_Evidence
0	British jets intercept 15 Russian military aircraft	10893901	British jets intercept 15 Russian military aircraft	News_and_Current_Events	International	N/A	High	The headline is direct and clearly states the event without ambiguity.	High	Covers a geopolitically relevant and timely topic concerning international military activities.	High	Uses clear, descriptive keywords like 'British jets', 'intercept', 'Russian military aircraft' which are highly relevant to the topic and discoverable.	Medium	While the event is specific, the phrasing is fairly standard for news reporting on military interceptions.	Yes	No	No	No	No	No	No	No	Adequate	46	No	Declarative Simple	It is a straightforward statement of fact, reporting an event without any special framing.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["British","Russian"]	No	[]	No		Yes	The mention of 'intercept' and 'military aircraft' implies a potential threat or escalating tensions.	No		No		No		No
1	New driveway rule change affecting every home in England has begun	10439139	New driveway rule change affecting every home in England has begun	News_and_Current_Events	Government	N/A	High	The headline is direct and easy to understand, clearly stating the what, who, and where.	High	The use of 'New' and 'has begun' creates a sense of immediacy and relevance for the target audience.	High	Uses specific and relevant keywords like 'driveway rule change' and 'England' that directly target a specific audience's potential interests.	Medium	While the topic is specific, the headline's structure is quite common for news alerts, lacking a highly unique angle.	No	No	No	No	No	No	No	No	Adequate	68	No	Declarative Simple	The headline makes a direct statement about a new event or situation without asking a question or using sensational language.	Yes	["begun"]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["England"]	No	[]	Yes	The headline creates an information gap by mentioning a 'new driveway rule change' without specifying what the change is, prompting the reader to click to find out.	Yes	The phrase 'affecting every home' can generate concern or fear among homeowners about potential negative consequences or obligations.	No		No		No		Yes	Directly appeals to residents of 'England' and specifically to those who are homeowners ('every home').
2	The historic English city that is the best day trip within one hour of London	10098169	The historic English city that is the best day trip within one hour of London	Travel	Destinations	Guides	High	The main message is very clear and easy to understand, directly stating the topic.	High	Day trips and proximity to major cities like London are evergreen topics with high interest.	High	Uses highly relevant keywords like "historic English city," "best day trip," and "one hour of London" which are likely search terms.	Medium	While "best day trip" is a common superlative, the specific geographic and historical context provides some differentiation.	Yes	No	No	No	No	No	No	No	Adequate	69	No	Superlative ('best', 'worst')	The headline uses the superlative "best" to describe the day trip experience.	No	[]	No	[]	No	[]	Yes	["best"]	No	[]	No	[]	Yes	["English","London"]	No	[]	Yes	The headline creates curiosity by promising the "best day trip" from London without immediately revealing the city.	No		No		No		Yes	The phrase "best day trip" evokes a sense of positive experience and an ideal outcome for readers seeking a trip.	Yes	The headline directly appeals to anyone interested in day trips from London, allowing them to easily identify with the topic.
3	David Mitchell convicted for covering road with potatoes and silt	10031250	David Mitchell convicted for covering road with potatoes and silt	News_and_Current_Events	Crime & Judicial	N/A	High	The headline clearly states who was convicted and for what unusual reason.	Low	The event is localized and not tied to a major ongoing news trend, making its general relevance low.	Low	The keywords are too specific to the event and do not align with common search queries.	High	The bizarre nature of the crime (covering a road with potatoes and silt) makes the headline highly original and memorable.	No	No	No	No	No	No	No	No	Adequate	65	No	Declarative Simple	The headline states a fact directly without questions, quotes, or other complex structures.	No	[]	No	[]	Yes	["convicted"]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	The unusual act of 'covering road with potatoes and silt' creates a strong information gap and makes the reader want to know the backstory.	No		Yes	The combination of 'potatoes and silt' as a method for a crime is unexpected and bizarre.	No		No		No
4	Say goodbye to parasols – Tesco is selling a smarter option that covers your entire outdoor space better	9765281	Say goodbye to parasols – Tesco is selling a smarter option that covers your entire outdoor space better	Home_and_Lifestyle	Gardening_and_Plants	N/A	High	The main message is straightforward and easy to grasp.	High	The topic of outdoor space solutions is relevant, especially during warmer seasons, and appeals to practical home improvement interests.	High	Keywords like "parasols", "Tesco", and "outdoor space" are relevant to the topic and target audience.	High	The headline positions the product as a "smarter option" and an improvement over traditional parasols, offering a unique angle.	No	No	No	No	Yes	No	No	No	Adequate	84	No	Comparative/Superlative	The headline compares a new "smarter option" to traditional "parasols", emphasizing its superior performance ("covers... better").	No	[]	No	[]	No	[]	Yes	["smarter option","better"]	No	[]	No	[]	No	[]	Yes	["Tesco"]	Yes	The phrase "smarter option that covers your entire outdoor space better" creates an information gap, prompting the reader to discover what this new solution is.	No		No		No		Yes	The headline offers a "smarter option" that performs "better," suggesting an improved solution to a common outdoor challenge, thereby instilling hope for a more effective product.	Yes	The phrase "Say goodbye to parasols" and reference to "your entire outdoor space" directly addresses the reader, implying a common problem they might face and offering a relevant solution.
5	Travellers descend on local park as much-loved community event cancelled after overnight encampment	9557677	Travellers descend on local park as much-loved community event cancelled after overnight encampment	News_and_Current_Events	Crime & Judicial	N/A	High	Clearly states the main events and their consequence.	High	Relates to a local community event and a timely disruption, highly relevant.	High	Uses specific and relevant keywords for local news interest.	Medium	The event is specific, but the headline structure is common for news of this nature.	No	No	No	No	Yes	No	No	No	Adequate	99	No	Declarative Simple	The headline directly informs the reader about an event and its cause without using questions, quotes, or urgency phrases.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No		Yes	community event cancelled after overnight encampment	No		Yes	Travellers descend on local park as much-loved community event cancelled after overnight encampment	No		Yes	local park, community event
6	Michael Schumacher, a tearful message from the clinic: "It was beautiful" – we will remember him forever	9470424	Michael Schumacher, a tearful message from the clinic: "It was beautiful" – we will remember him forever	Sports	Motorsports (F1, MotoGP)	N/A	High	The main message is easy to understand, conveying emotion and a sense of finality regarding Michael Schumacher.	High	Connects with global interest in a highly recognized figure, evoking strong emotional engagement related to his legacy.	High	Uses "Michael Schumacher" as a strong primary keyword, alongside emotionally resonant phrases like "tearful message" and "remember him forever".	High	The direct quote and the emotional framing ("tearful message," "we will remember him forever") provide a unique and impactful angle.	No	Yes	No	Yes	Yes	No	No	No	Adequate	90	No	Direct Quote	The headline features a direct quote ("It was beautiful") and attributes it to Michael Schumacher from the clinic, making it a direct quote type.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	The phrases "a tearful message from the clinic" and "It was beautiful" create an information gap, making readers curious about the context and meaning behind the message.	Yes	The mention of "clinic" and the implicit finality conveyed by "we will remember him forever" can evoke concern for his ongoing health condition and future.	No		No		No		Yes	Many readers would identify with the feeling of remembering a beloved figure, fostering empathy and shared sentiment.
7	Gardeners face £5,000 fine for mowing lawn on Saturday and Sunday	9365831	Gardeners face £5,000 fine for mowing lawn on Saturday and Sunday	Home_and_Lifestyle	Gardening_and_Plants	N/A	High	The main message is very clear and direct, easy to understand.	High	Gardening and local regulations are topics of high general interest, especially regarding common weekend activities.	High	Keywords like "Gardeners", "fine", "mowing lawn", "Saturday and Sunday" are highly relevant and likely to attract attention.	Medium	While the topic of fines is not new, the specific amount (£5,000) and the weekend restriction offer a somewhat unique angle.	Yes	No	No	No	No	No	No	No	Adequate	66	No	Declarative Simple	The headline presents a direct statement of fact regarding a potential fine for an action.	No	[]	No	[]	No	[]	No	[]	Yes	["£5,000","fine"]	Yes	["fine for mowing lawn on Saturday and Sunday"]	No	[]	No	[]	Yes	The headline sparks curiosity about why gardeners face such a large fine for mowing on those specific days, and where this rule applies.	Yes	The mention of a "£5,000 fine" triggers concern for gardeners about potential penalties for common activities.	Yes	A "£5,000 fine" for mowing a lawn on a weekend is surprisingly high and might evoke a sense of shock or disbelief.	Yes	The headline could provoke indignation, as many might view a fine for mowing a lawn on a weekend as an excessive or unreasonable restriction.	No		Yes	The headline directly appeals to "Gardeners" and anyone who mows their lawn, especially on weekends.
8	Households urged to put sheet of A4 paper in fridge before Saturday	9220647	Households urged to put sheet of A4 paper in fridge before Saturday	Home_and_Lifestyle	Hacks	Energy Saving	High	The instruction is clear and easy to understand.	High	Provides a specific, time-sensitive instruction relevant to household management, likely energy saving.	High	Uses direct and relevant keywords like 'Households', 'fridge', 'A4 paper' that target the audience and topic.	High	The unusual instruction 'put sheet of A4 paper in fridge' makes the headline highly original and creates curiosity.	Yes	No	No	No	No	No	No	No	Adequate	64	No	Declarative Simple	The headline presents a straightforward statement advising an action without questions or strong emotional punctuation.	Yes	["before","Saturday"]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	The unusual and unexplained action of putting 'A4 paper in fridge' before a specific deadline strongly triggers curiosity, making readers wonder why and what the benefit is.	No		Yes	The instruction itself is surprising due to its unconventional nature.	No		No		Yes	Directly addresses 'Households', making it highly relatable to a broad audience.
9	Lando Norris leads tributes as popular F1 presenter retires after cancer diagnosis	9175453	Lando Norris leads tributes as popular F1 presenter retires after cancer diagnosis	Sports	Motorsports (F1, MotoGP)	News	High	The message is direct and easy to understand, clearly stating the subject and the event.	High	The news involves a well-known personality in a popular sport (F1) and deals with a sensitive, high-interest human topic.	High	Uses highly relevant and searchable keywords like "Lando Norris", "F1", and "cancer diagnosis", which attract a specific and broad audience.	Low	It's a standard and informative news headline formulation, lacking a unique or creative angle.	No	No	No	No	No	No	No	No	Adequate	88	No	Declarative Simple	The headline states a fact or event directly without resorting to questions, superlatives, or other complex structures.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["F1"]	No		Yes	The mention of "cancer diagnosis" generates concern and empathy for the presenter.	No		No		No		Yes	Appeals to followers of F1 and fans of the personalities mentioned, creating a sense of community and shared feeling.

	Title	Visibility	Cleaned_Headline	Main_Category	Subcategory_1	Subcategory_2	Clarity_and_Conciseness_Value	Clarity_and_Conciseness_Comment	Relevance_and_Timeliness_Value	Relevance_and_Timeliness_Comment	Strategic_Keyword_Usage_Value	Strategic_Keyword_Usage_Comment	Originality_and_Differentiation_Value	Originality_and_Differentiation_Comment	Contains_Numbers	Contains_Quotes	Contains_Question_Mark	Contains_Colon	Contains_Hyphen	Contains_Exclamation_Mark	Starts_With_Number	Ends_With_Question_Mark	Length_General_Assessment	Length_Number_of_Characters	Emphatic_Capitalization_Usage	Main_Classification	Comment_Type_Justification	Temporal_Urgency_Present	Temporal_Urgency_Words	Exclusivity_Present	Exclusivity_Words	Authority_Present	Authority_Words	Solution_Present	Solution_Words	Economic_Benefit_Present	Economic_Benefit_Words	Prohibition_Restriction_Present	Prohibition_Restriction_Words	National_Relevance_Present	National_Relevance_Words	Recognized_Brand_Present	Recognized_Brand_Words	Curiosity_Present	Curiosity_Evidence	Fear_Concern_Present	Fear_Concern_Evidence	Surprise_Awe_Present	Surprise_Awe_Evidence	Indignation_Controversy_Present	Indignation_Controversy_Evidence	Hope_Optimism_Present	Hope_Optimism_Evidence	Personal_Identification_Present	Personal_Identification_Evidence
989	270 home plans approved in Surrey after inspector concludes a nearby 'town' is actually a village	320207	270 home plans approved in Surrey after inspector concludes a nearby 'town' is actually a village	News_and_Current_Events	Environment	N/A	High	The main message is easy and quick to understand, clearly stating the outcome and the reason.	High	Local development news is highly relevant to residents and communities in the area mentioned, addressing a specific local issue.	High	Uses direct and relevant keywords such as "home plans", "approved", "Surrey", "inspector", "town", and "village" that are likely to be searched for by a local audience.	Medium	While the structure is common, the specific detail about the "town" actually being a "village" provides a unique and potentially contentious angle that differentiates it.	Yes	Yes	No	No	No	No	Yes	No	Adequate	92	No	Declarative Simple	The headline directly states a completed action and its contributing factors without using questions, commands, or dramatic framing.	No	[]	No	[]	Yes	["inspector","concludes"]	No	[]	No	[]	No	[]	Yes	["Surrey"]	No	[]	Yes	The distinction between 'town' and 'village' and its impact on the approval of 270 home plans creates an information gap, making readers curious about the significance of this reclassification.	No		No		Yes	The headline implies a dispute or reclassification ('town' is actually a 'village') that led to a significant decision (270 home plans approved), which could spark debate or indignation among those affected by or interested in local planning.	No		Yes	Residents of Surrey or the specific 'town'/'village' mentioned would identify with the local impact of this decision, as it directly affects their community and living environment.
990	‘It’s goodbye to French fishermen’: Macron under pressure as crucial UN ocean summit opens	319502	‘It’s goodbye to French fishermen’: Macron under pressure as crucial UN ocean summit opens	News_and_Current_Events	Politics	Environment	High	The main message regarding the situation of French fishermen and Macron's pressure in the context of the UN summit is clear and easy to understand.	High	The mention of a "crucial UN ocean summit opens" indicates high current relevance and timeliness.	High	Uses highly relevant keywords like "French fishermen", "Macron", and "UN ocean summit" which are specific to the topic and likely to appeal to the target audience.	Medium	While reporting on a current event, the direct quote and specific focus provide a distinct angle, though the phrasing is not exceptionally unique.	No	Yes	No	Yes	No	No	No	No	Adequate	91	No	Direct Quote/Attribution	The headline starts with a direct quote, followed by a colon and the context, which attributes the sentiment or statement.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["French"]	No	[]	Yes	The phrase "It’s goodbye to French fishermen" creates an information gap, prompting the reader to seek the reasons behind it.	Yes	The potential loss for "French fishermen" and "Macron under pressure" evoke concern about negative consequences and difficulties.	No		Yes	The situation of fishermen and political pressure at a summit can easily spark debate and strong opinions, suggesting potential conflict or injustice.	No		Yes	The mention of "French fishermen" directly appeals to individuals within that group or those concerned with national industries and political outcomes.
991	Ruth Langsford styles Broderie Anglaise blouse with trending turn-up jeans to create a breezy smart-casual look	319337	Ruth Langsford styles Broderie Anglaise blouse with trending turn-up jeans to create a breezy smart-casual look	Fashion	Style Tips	N/A	High	The main message about Ruth Langsford's outfit and its style is easy to understand.	High	Fashion is an evergreen topic, and the mention of "trending" adds timeliness. Celebrity endorsement increases relevance.	High	Uses relevant keywords like "Ruth Langsford", "Broderie Anglaise blouse", "trending turn-up jeans", and "smart-casual look" that are appealing for fashion-interested audiences.	Medium	While featuring a celebrity, the headline describes a common fashion topic in a straightforward manner, lacking a highly unique angle.	No	No	No	No	Yes	No	No	No	Adequate	108	No	Declarative Simple	The headline makes a clear, straightforward statement about a fashion choice without posing a question or implying urgency.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Ruth Langsford"]	Yes	The mention of "trending turn-up jeans" and the description of "breezy smart-casual look" can pique curiosity about the specific style.	No		No		No		No		Yes	Readers interested in fashion or Ruth Langsford's style might identify with the desire to replicate the described look.
992	Scottish government to remove WhatsApp from phones	318561	Scottish government to remove WhatsApp from phones	News_and_Current_Events	Politics	Government	High	The main message is direct and easy to understand.	High	Government actions regarding widely used communication apps are highly relevant to the general public.	High	Key terms like "Scottish government" and "WhatsApp" are present, attracting relevant audience interest.	High	The action described is significant and unusual, making the headline stand out.	No	No	No	No	No	No	No	No	Adequate	46	No	Declarative Simple	The headline presents a clear and direct statement of an action to be taken by the Scottish government.	No	[]	No	[]	Yes	["government"]	No	[]	No	[]	Yes	["remove"]	Yes	["Scottish"]	Yes	["WhatsApp"]	Yes	The headline creates an information gap: why is the Scottish government removing WhatsApp and what are the implications?	Yes	Users of WhatsApp, especially those in Scotland, might feel concern over the potential loss of a communication tool or privacy implications.	Yes	A government taking direct action to remove a widely used app from phones is an unexpected and notable event.	Yes	Such a government decision regarding a popular app is likely to stir debate and strong opinions among the public.	No		Yes	The headline directly impacts individuals who use WhatsApp in Scotland.
993	All Virgin Media customers get big free TV upgrade with two new channels	318074	All Virgin Media customers get big free TV upgrade with two new channels	Entertainment_and_Culture	Series & Platforms	N/A	High	The main message is very clear and easy to understand, directly stating the benefit.	High	Highly relevant for existing Virgin Media customers and those interested in TV services.	High	Uses direct and appealing keywords like "Virgin Media", "free TV upgrade", and "new channels".	Medium	While a common type of announcement, it is specific to a well-known brand and offers a clear benefit.	Yes	No	No	No	No	No	No	No	Adequate	59	No	Declarative Simple	The headline simply states a fact about an upgrade for Virgin Media customers.	No	[]	No	[]	No	[]	No	[]	Yes	["free"]	No	[]	No	[]	Yes	["Virgin Media"]	Yes	The phrase "big free TV upgrade" and "two new channels" creates curiosity about the specific benefits and channel names.	No		No		No		Yes	The promise of a "free TV upgrade" and "new channels" evokes positive feelings and optimism for current customers.	Yes	The headline directly targets and identifies with "All Virgin Media customers", making it highly relevant to that group.
994	Airport's £100m extension opens to passengers	317796	Airport's £100m extension opens to passengers	Travel	Planning & Tips	N/A	High	The main message is easy and quick to understand, with no ambiguity.	High	Airport developments are highly relevant to current interests of travelers and local communities.	Medium	Uses relevant keywords like "Airport", "extension", and "passengers", with "£100m" indicating significant investment.	Low	This is a fairly standard news headline for an infrastructure project, lacking a unique angle.	Yes	No	No	No	No	No	No	No	Adequate	46	No	Declarative Simple	The headline states a clear fact directly and simply without any special formatting or emotional appeals.	No	[]	No	[]	No	[]	No	[]	Yes	["£100m"]	No	[]	No	[]	No	[]	No		No		No		No		Yes	The opening of an "extension" suggests progress and improved services for travelers.	Yes	The word "passengers" directly appeals to individuals who travel or plan to travel.
995	Warning issued after three dogs rescued from hot car in Aylesbury	317685	Warning issued after three dogs rescued from hot car in Aylesbury	Public_Safety	Alerts & Prevention	N/A	High	The message is clear and direct, detailing a warning, the rescue of dogs, the dangerous situation, and the location.	High	Animal welfare, particularly in dangerous situations like hot cars, is a consistently relevant and timely topic, especially during warmer periods.	High	Keywords like "Warning", "dogs", "rescued", and "hot car" are highly relevant and likely to attract an audience interested in animal welfare and local news.	Medium	While "dogs in hot car" incidents are common, the specific detail of a "Warning issued" and the local context of "Aylesbury" offer a moderate level of differentiation.	Yes	No	No	No	No	No	No	No	Adequate	65	No	Declarative Simple	The headline directly states a factual event without posing a question, quoting anyone, or implying urgency beyond the event itself.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Aylesbury"]	No	[]	No		Yes	The phrase "Warning issued" implies a potential threat or danger, and "hot car" evokes concern for the dogs' well-being.	No		Yes	The act of leaving dogs in a "hot car" typically provokes indignation towards the responsible party.	Yes	The word "rescued" offers a positive resolution to the dangerous situation, instilling a sense of hope.	No
996	Britain's newest pedigree dog breed is rare, cuddly and curly-coated	317591	Britain's newest pedigree dog breed is rare, cuddly and curly-coated	Home_and_Lifestyle	Pets	N/A	High	The main message is clear and easy to understand.	High	Pets and new breeds are topics of high and evergreen interest.	High	Uses relevant keywords like "pedigree dog breed," "rare," "cuddly," and "curly-coated."	Medium	Describes a new breed, which is somewhat unique, but the phrasing is largely descriptive.	No	No	No	No	Yes	No	No	No	Adequate	59	No	Declarative Simple	The headline makes a straightforward factual statement about a new dog breed.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Britain's"]	No	[]	Yes	The headline sparks curiosity about what this new, rare breed is and its characteristics.	No		No		No		No		Yes	Dog lovers and pet enthusiasts may identify with the appeal of a new, cuddly breed.
997	British Gas, EDF, EON, OVO and Octopus customers urged to act before Monday	316533	British Gas, EDF, EON, OVO and Octopus customers urged to act before Monday	Finance_and_Business	Companies & Entrepreneurship	N/A	High	The message is direct and easy to understand, clearly stating who needs to act and when.	High	The headline addresses major energy providers and includes a specific deadline, making it highly relevant and timely for a large segment of the population.	High	The names of the energy companies serve as strong keywords, directly targeting their customer base. "Customers" and "act before Monday" also enhance relevance and urgency.	Medium	While the structure is straightforward, the specific mention of multiple prominent energy providers and a clear deadline helps it stand out from more generic headlines.	No	No	No	No	No	No	No	No	Adequate	69	No	Urgency	The phrase "urged to act before Monday" explicitly conveys a time-sensitive call to action, emphasizing urgency.	Yes	["act","before Monday"]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["British Gas","EDF","EON","OVO","Octopus"]	Yes	["British Gas","EDF","EON","OVO","Octopus"]	No		Yes	The urgent call to "act before Monday" implicitly suggests potential negative consequences or missed opportunities if the reader fails to comply.	No		No		No		Yes	The headline directly addresses "customers" of major energy companies, ensuring a high degree of personal relevance for a significant portion of the audience.
998	Weekend walk: visit three stunning waterfalls and a village pub	316132	Weekend walk: visit three stunning waterfalls and a village pub	Travel	Destinations	Guides	High	The main message is very clear and easy to understand.	High	This is an evergreen topic that appeals to individuals seeking leisure activities and scenic outings, especially on weekends.	High	Keywords like "weekend walk," "waterfalls," and "village pub" are highly relevant and appealing to an audience interested in travel, nature, and leisure.	Medium	While the concept of weekend walks is common, the specific combination of "three stunning waterfalls and a village pub" offers a distinct and appealing angle.	Yes	No	No	Yes	No	No	No	No	Adequate	59	No	Declarative Simple	The headline presents a straightforward statement, declaring an activity and its appealing elements without posing a question or making a strong claim of urgency, mystery, or comparison.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	The mention of "three stunning waterfalls" and "a village pub" creates curiosity about the specific locations and what makes them stunning.	No		Yes	The word "stunning" aims to evoke a sense of awe or wonder at the described locations.	No		Yes	Suggests a pleasant and enjoyable activity for the "weekend", promoting a positive outlook and the anticipation of a good experience.	Yes	Appeals directly to anyone looking for a relaxing and scenic "weekend walk" and a traditional "pub" experience.

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